Initial commit: Lush vs Bash AI benchmarking framework

Benchmark harness that uses LLM agents to solve shell scripting tasks
in both Bash and Lush, then compares correctness and code quality.

- CLI with run, run-all, list-tasks, report, and export commands
- Agent loop with retry support via Anthropic Claude provider
- Test harness executing solutions in sandboxed subprocesses
- LLM-driven questionnaire for subjective code quality evaluation
- HTML report export with charts (matplotlib)
- 8 Category A tasks (write-from-scratch in both languages)
- 4 Category B tasks (verify provided Bash, convert to Lush)
- Lush language reference for agent context

.gitignore

@@ -0,0 +1,16 @@
+#
+.env
+
+# Python-generated files
+__pycache__/
+*.py[oc]
+build/
+dist/
+wheels/
+*.egg-info
+
+# Virtual environments
+.venv
+
+# Results output
+results/

.python-version

@@ -0,0 +1 @@
+3.11

config.toml

@@ -0,0 +1,15 @@
+[lush]
+binary = "/Users/nik/Code/20251000_lush/lush"
+
+[agent]
+max_retries = 3
+timeout_seconds = 10
+normalize_whitespace = true
+
+[results]
+output_dir = "results"
+
+[anthropic]
+api_key_env = "ANTHROPIC_API_KEY"
+model = "claude-sonnet-4-20250514"
+max_tokens = 4096

lush_bench/agent.py

@@ -0,0 +1,164 @@
+from __future__ import annotations
+
+import re
+from pathlib import Path
+
+from .config import Config
+from .harness import evaluate
+from .models import LanguageResult, Task, TestCase
+from .providers.base import LLMProvider, Message
+from .questionnaire import run_questionnaire
+
+LUSH_REFERENCE_PATH = Path(__file__).parent.parent / "lush_reference.md"
+
+
+def load_lush_reference() -> str:
+    return LUSH_REFERENCE_PATH.read_text()
+
+
+def extract_code(response: str, language: str) -> str | None:
+    """Extract the last fenced code block from the response."""
+    if language == "bash":
+        patterns = [r"```(?:bash|sh)\n(.*?)```", r"```\n(.*?)```"]
+    else:
+        patterns = [r"```(?:lua|lush)\n(.*?)```", r"```\n(.*?)```"]
+
+    for pattern in patterns:
+        matches = re.findall(pattern, response, re.DOTALL)
+        if matches:
+            return matches[-1].strip()
+    return None
+
+
+def build_system_prompt(language: str) -> str:
+    base = (
+        "You are a skilled programmer. Write solutions that read from stdin and write to stdout. "
+        "Output ONLY the code in a single fenced code block. No explanations."
+    )
+    if language == "lush":
+        ref = load_lush_reference()
+        return f"{base}\n\nYou are writing in lush, a Lua-based shell language. Here is the language reference:\n\n{ref}"
+    return f"{base}\n\nYou are writing in bash."
+
+
+def _describe_test_case(tc: TestCase, index: int) -> str:
+    """Build a human-readable description of a test case for the agent."""
+    parts = [f"Test case {index}:"]
+    if tc.stdin:
+        parts.append(f"  Input (stdin):\n{tc.stdin}")
+    if tc.env:
+        parts.append(f"  Environment variables: {tc.env}")
+    if tc.setup_files:
+        for fname, content in tc.setup_files.items():
+            parts.append(f"  File in working directory ({fname}):\n{content}")
+    if tc.expected_stdout:
+        parts.append(f"  Expected stdout:\n{tc.expected_stdout}")
+    if tc.expected_files:
+        for fname, content in tc.expected_files.items():
+            parts.append(f"  Expected file ({fname}):\n{content}")
+    return "\n".join(parts)
+
+
+def build_task_prompt(task: Task, language: str) -> str:
+    prompt = f"Task: {task.name}\n\n{task.description}\n\n"
+    prompt += "Your script runs in an isolated working directory. "
+    prompt += "Any files listed as setup files will exist in that directory before your script runs.\n\n"
+    prompt += "Example test cases:\n"
+    for i, tc in enumerate(task.test_cases[:2]):  # Show first 2 as examples
+        prompt += "\n" + _describe_test_case(tc, i) + "\n"
+    lang_label = "bash" if language == "bash" else "lua"
+    prompt += f"\nWrite the solution in a ```{lang_label} code block."
+    return prompt
+
+
+def build_conversion_prompt(task: Task) -> str:
+    prompt = f"Task: {task.name}\n\n{task.description}\n\n"
+    prompt += f"Here is the bash source to convert to lush (Lua-based shell):\n\n```bash\n{task.bash_source}\n```\n\n"
+    prompt += "Example test cases:\n"
+    for i, tc in enumerate(task.test_cases[:2]):
+        prompt += f"\nInput:\n{tc.stdin}\nExpected output:\n{tc.expected_stdout}\n"
+    prompt += "\nConvert this to lush. Write the solution in a ```lua code block."
+    return prompt
+
+
+def build_failure_feedback(test_results: list, task: Task) -> str:
+    lines = ["Your solution failed some test cases:\n"]
+    for tr in test_results:
+        if not tr.passed:
+            tc = task.test_cases[tr.test_case_index]
+            lines.append(f"Test case {tr.test_case_index}:")
+            lines.append(f"  Input: {tc.stdin!r}")
+            lines.append(f"  Expected stdout: {tc.expected_stdout!r}")
+            lines.append(f"  Got stdout: {tr.actual_stdout!r}")
+            if tr.stderr:
+                lines.append(f"  Stderr: {tr.stderr!r}")
+            if tc.env:
+                lines.append(f"  Environment vars: {tc.env}")
+            if tc.setup_files:
+                lines.append(f"  Files in working directory: {list(tc.setup_files.keys())}")
+            for fname, mismatch in tr.file_mismatches.items():
+                lines.append(f"  File {fname!r}: expected {mismatch['expected']!r}, got {mismatch['actual']!r}")
+            lines.append("")
+    lines.append("Please fix your solution. Output ONLY the corrected code in a fenced code block.")
+    return "\n".join(lines)
+
+
+def solve_task(
+    provider: LLMProvider,
+    task: Task,
+    language: str,
+    config: Config,
+) -> LanguageResult:
+    """Run the agent loop: prompt -> code -> test -> retry."""
+    system = build_system_prompt(language)
+
+    if task.category == "b" and language == "lush":
+        user_prompt = build_conversion_prompt(task)
+    else:
+        user_prompt = build_task_prompt(task, language)
+
+    messages: list[Message] = [Message(role="user", content=user_prompt)]
+    turns = 0
+
+    for attempt in range(1 + config.max_retries):
+        turns += 1
+        response = provider.send(messages, system=system)
+        messages.append(Message(role="assistant", content=response))
+
+        code = extract_code(response, language)
+        if code is None:
+            if attempt < config.max_retries:
+                feedback = "I couldn't find a code block in your response. Please provide your solution in a fenced code block."
+                messages.append(Message(role="user", content=feedback))
+                continue
+            return LanguageResult(
+                language=language,
+                solution_code="",
+                test_results=[],
+                all_passed=False,
+                agent_turns=turns,
+            )
+
+        test_results = evaluate(task, code, language, config)
+        all_passed = all(tr.passed for tr in test_results)
+
+        if all_passed or attempt == config.max_retries:
+            return LanguageResult(
+                language=language,
+                solution_code=code,
+                test_results=test_results,
+                all_passed=all_passed,
+                agent_turns=turns,
+            )
+
+        feedback = build_failure_feedback(test_results, task)
+        messages.append(Message(role="user", content=feedback))
+
+    # Should not reach here, but just in case
+    return LanguageResult(
+        language=language,
+        solution_code=code if code else "",
+        test_results=test_results if test_results else [],
+        all_passed=False,
+        agent_turns=turns,
+    )

lush_bench/config.py

@@ -0,0 +1,39 @@
+from __future__ import annotations
+
+import tomllib
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Any
+
+
+@dataclass
+class Config:
+    lush_binary: Path
+    max_retries: int = 3
+    timeout_seconds: float = 10.0
+    normalize_whitespace: bool = True
+    output_dir: Path = Path("results")
+    provider_configs: dict[str, dict[str, Any]] = field(default_factory=dict)
+
+    @classmethod
+    def load(cls, path: Path | None = None) -> Config:
+        if path is None:
+            path = Path(__file__).parent.parent / "config.toml"
+        raw = tomllib.loads(path.read_text())
+
+        lush = raw.get("lush", {})
+        agent = raw.get("agent", {})
+        results = raw.get("results", {})
+
+        # Collect provider configs (any top-level section not in known keys)
+        known_sections = {"lush", "agent", "results"}
+        provider_configs = {k: v for k, v in raw.items() if k not in known_sections and isinstance(v, dict)}
+
+        return cls(
+            lush_binary=Path(lush["binary"]),
+            max_retries=agent.get("max_retries", 3),
+            timeout_seconds=agent.get("timeout_seconds", 10.0),
+            normalize_whitespace=agent.get("normalize_whitespace", True),
+            output_dir=Path(results.get("output_dir", "results")),
+            provider_configs=provider_configs,
+        )

lush_bench/export.py

@@ -0,0 +1,307 @@
+from __future__ import annotations
+
+import base64
+import html
+import io
+from pathlib import Path
+
+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+import matplotlib.ticker as ticker
+
+from .models import BenchmarkResult
+from .report import (
+    LIKERT_QUESTIONS,
+    _get_freeform,
+    _get_likert_scores,
+    _parse_likert,
+    load_latest_results,
+)
+
+BASH_COLOR = "#4E79A7"
+LUSH_COLOR = "#E15759"
+NEUTRAL_COLOR = "#999999"
+
+
+def _fig_to_base64(fig: plt.Figure) -> str:
+    buf = io.BytesIO()
+    fig.savefig(buf, format="png", dpi=150, bbox_inches="tight", facecolor="white")
+    plt.close(fig)
+    buf.seek(0)
+    return base64.b64encode(buf.read()).decode()
+
+
+def _aggregate_likert(results: list[BenchmarkResult]) -> dict[str, dict[str, float]]:
+    """Return {question_key: {bash: avg, lush: avg}}."""
+    agg: dict[str, dict[str, list[float]]] = {}
+    for key, _ in LIKERT_QUESTIONS:
+        agg[key] = {"bash": [], "lush": []}
+    for r in results:
+        scores = _get_likert_scores(r)
+        for key in scores:
+            for lang in ("bash", "lush"):
+                val = scores[key][lang]
+                if val is not None:
+                    agg[key][lang].append(val)
+    return {
+        key: {
+            lang: (sum(vals) / len(vals)) if vals else 0.0
+            for lang, vals in agg[key].items()
+        }
+        for key in agg
+    }
+
+
+def chart_questionnaire_comparison(results: list[BenchmarkResult]) -> str:
+    """Grouped horizontal bar chart comparing bash vs lush on each Likert metric."""
+    avgs = _aggregate_likert(results)
+    labels = [label for _, label in LIKERT_QUESTIONS]
+    bash_vals = [avgs[key]["bash"] for key, _ in LIKERT_QUESTIONS]
+    lush_vals = [avgs[key]["lush"] for key, _ in LIKERT_QUESTIONS]
+
+    fig, ax = plt.subplots(figsize=(8, 4.5))
+    y = range(len(labels))
+    bar_h = 0.35
+    bars_bash = ax.barh([i + bar_h / 2 for i in y], bash_vals, bar_h, label="bash", color=BASH_COLOR)
+    bars_lush = ax.barh([i - bar_h / 2 for i in y], lush_vals, bar_h, label="lush", color=LUSH_COLOR)
+
+    ax.set_yticks(list(y))
+    ax.set_yticklabels(labels)
+    ax.set_xlim(0, 5.5)
+    ax.xaxis.set_major_locator(ticker.MultipleLocator(1))
+    ax.set_xlabel("Score (1-5)")
+    ax.set_title("Questionnaire Scores: Bash vs Lush")
+    ax.legend(loc="lower right")
+    ax.invert_yaxis()
+
+    for bar in bars_bash:
+        w = bar.get_width()
+        ax.text(w + 0.08, bar.get_y() + bar.get_height() / 2, f"{w:.1f}", va="center", fontsize=8)
+    for bar in bars_lush:
+        w = bar.get_width()
+        ax.text(w + 0.08, bar.get_y() + bar.get_height() / 2, f"{w:.1f}", va="center", fontsize=8)
+
+    ax.grid(axis="x", alpha=0.3)
+    return _fig_to_base64(fig)
+
+
+def chart_turns_comparison(results: list[BenchmarkResult]) -> str:
+    """Bar chart of agent turns per task for bash vs lush."""
+    # Only include tasks where the agent actually solved (turns > 0)
+    cat_a = [r for r in results if r.category == "a"]
+    names = [r.task_name for r in cat_a]
+    bash_turns = [r.bash_result.agent_turns if r.bash_result else 0 for r in cat_a]
+    lush_turns = [r.lush_result.agent_turns if r.lush_result else 0 for r in cat_a]
+
+    fig, ax = plt.subplots(figsize=(8, 4))
+    x = range(len(names))
+    bar_w = 0.35
+    ax.bar([i - bar_w / 2 for i in x], bash_turns, bar_w, label="bash", color=BASH_COLOR)
+    ax.bar([i + bar_w / 2 for i in x], lush_turns, bar_w, label="lush", color=LUSH_COLOR)
+
+    ax.set_xticks(list(x))
+    ax.set_xticklabels(names, rotation=35, ha="right", fontsize=8)
+    ax.set_ylabel("Agent Turns")
+    ax.set_title("Agent Turns to Solve (Category A)")
+    ax.yaxis.set_major_locator(ticker.MaxNLocator(integer=True))
+    ax.legend()
+    ax.grid(axis="y", alpha=0.3)
+    return _fig_to_base64(fig)
+
+
+def chart_per_task_heatmap(results: list[BenchmarkResult]) -> str:
+    """Heatmap showing lush-minus-bash score diff per task and metric."""
+    labels = [label for _, label in LIKERT_QUESTIONS]
+    tasks = [r.task_name for r in results]
+
+    data: list[list[float]] = []
+    for r in results:
+        scores = _get_likert_scores(r)
+        row = []
+        for key, _ in LIKERT_QUESTIONS:
+            b = scores[key]["bash"]
+            l = scores[key]["lush"]
+            if b is not None and l is not None:
+                row.append(l - b)
+            else:
+                row.append(0.0)
+        data.append(row)
+
+    fig, ax = plt.subplots(figsize=(8, max(4, len(tasks) * 0.45 + 1)))
+    im = ax.imshow(data, cmap="RdYlGn", aspect="auto", vmin=-3, vmax=3)
+
+    ax.set_xticks(range(len(labels)))
+    ax.set_xticklabels(labels, rotation=35, ha="right", fontsize=8)
+    ax.set_yticks(range(len(tasks)))
+    ax.set_yticklabels(tasks, fontsize=8)
+
+    for i in range(len(tasks)):
+        for j in range(len(labels)):
+            val = data[i][j]
+            text = f"+{val:.0f}" if val > 0 else f"{val:.0f}" if val < 0 else "0"
+            ax.text(j, i, text, ha="center", va="center", fontsize=8,
+                    color="white" if abs(val) >= 2 else "black")
+
+    ax.set_title("Score Difference (Lush - Bash)")
+    fig.colorbar(im, ax=ax, shrink=0.8, label="Lush advantage")
+    return _fig_to_base64(fig)
+
+
+def _build_summary_html(results: list[BenchmarkResult]) -> str:
+    rows = []
+    for r in results:
+        b = r.bash_result
+        l = r.lush_result
+        b_cls = "pass" if b and b.all_passed else "fail"
+        l_cls = "pass" if l and l.all_passed else "fail"
+        b_pass = "PASS" if b and b.all_passed else "FAIL"
+        l_pass = "PASS" if l and l.all_passed else "FAIL"
+        b_turns = str(b.agent_turns) if b else "-"
+        l_turns = str(l.agent_turns) if l else "-"
+        rows.append(f"""<tr>
+            <td>{html.escape(r.task_name)}</td><td>{r.category.upper()}</td>
+            <td class="{b_cls}">{b_pass}</td><td>{b_turns}</td>
+            <td class="{l_cls}">{l_pass}</td><td>{l_turns}</td>
+        </tr>""")
+
+    b_passed = sum(1 for r in results if r.bash_result and r.bash_result.all_passed)
+    l_passed = sum(1 for r in results if r.lush_result and r.lush_result.all_passed)
+    total = len(results)
+
+    return f"""<table>
+        <thead><tr>
+            <th>Task</th><th>Cat</th>
+            <th>Bash</th><th>Turns</th>
+            <th>Lush</th><th>Turns</th>
+        </tr></thead>
+        <tbody>{"".join(rows)}</tbody>
+        <tfoot><tr>
+            <td><strong>Total</strong></td><td></td>
+            <td><strong>{b_passed}/{total}</strong></td><td></td>
+            <td><strong>{l_passed}/{total}</strong></td><td></td>
+        </tr></tfoot>
+    </table>"""
+
+
+def _build_detail_html(results: list[BenchmarkResult]) -> str:
+    sections = []
+    for r in results:
+        b_status = "PASS" if r.bash_result and r.bash_result.all_passed else "FAIL"
+        l_status = "PASS" if r.lush_result and r.lush_result.all_passed else "FAIL"
+
+        scores = _get_likert_scores(r)
+        score_rows = []
+        for key, label in LIKERT_QUESTIONS:
+            b_val = scores[key]["bash"]
+            l_val = scores[key]["lush"]
+            b_str = f"{b_val:.0f}" if b_val is not None else "-"
+            l_str = f"{l_val:.0f}" if l_val is not None else "-"
+            if b_val is not None and l_val is not None:
+                d = l_val - b_val
+                d_str = f"+{d:.0f}" if d > 0 else f"{d:.0f}"
+                d_cls = "pos" if d > 0 else "neg" if d < 0 else ""
+            else:
+                d_str = "-"
+                d_cls = ""
+            score_rows.append(f'<tr><td>{html.escape(label)}</td>'
+                              f'<td>{b_str}</td><td>{l_str}</td>'
+                              f'<td class="{d_cls}">{d_str}</td></tr>')
+
+        obs = _get_freeform(r)
+        obs_html = ""
+        for lang, text in obs.items():
+            obs_html += f'<p><strong>{lang}:</strong> {html.escape(text)}</p>\n'
+
+        sections.append(f"""
+        <div class="task-detail">
+            <h3>{html.escape(r.task_name)} <span class="cat">[{r.category}]</span>
+                <span class="{"pass" if b_status == "PASS" else "fail"}">bash={b_status}</span>
+                <span class="{"pass" if l_status == "PASS" else "fail"}">lush={l_status}</span>
+            </h3>
+            <table class="scores">
+                <thead><tr><th>Metric</th><th>Bash</th><th>Lush</th><th>Diff</th></tr></thead>
+                <tbody>{"".join(score_rows)}</tbody>
+            </table>
+            <div class="observations">{obs_html}</div>
+        </div>""")
+
+    return "\n".join(sections)
+
+
+def export_html(results_dir: Path, output_path: Path) -> None:
+    results = load_latest_results(results_dir)
+    if not results:
+        output_path.write_text("<html><body><p>No results found.</p></body></html>")
+        return
+
+    chart_questionnaire = chart_questionnaire_comparison(results)
+    chart_turns = chart_turns_comparison(results)
+    chart_heatmap = chart_per_task_heatmap(results)
+    summary_table = _build_summary_html(results)
+    detail_html = _build_detail_html(results)
+
+    model = results[0].model if results else "unknown"
+    timestamp = max(r.timestamp for r in results)
+
+    page = f"""<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="utf-8">
+<title>Lush vs Bash Benchmark Report</title>
+<style>
+    :root {{ --bash: {BASH_COLOR}; --lush: {LUSH_COLOR}; }}
+    * {{ box-sizing: border-box; margin: 0; padding: 0; }}
+    body {{ font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, sans-serif;
+           max-width: 960px; margin: 40px auto; padding: 0 20px; color: #1a1a1a; line-height: 1.5; }}
+    h1 {{ font-size: 1.8rem; margin-bottom: 4px; }}
+    h2 {{ font-size: 1.3rem; margin: 32px 0 16px; border-bottom: 2px solid #e0e0e0; padding-bottom: 6px; }}
+    h3 {{ font-size: 1.05rem; margin-bottom: 10px; }}
+    .meta {{ color: #666; font-size: 0.9rem; margin-bottom: 24px; }}
+    table {{ border-collapse: collapse; width: 100%; margin: 12px 0 20px; font-size: 0.9rem; }}
+    th, td {{ padding: 8px 12px; text-align: left; border-bottom: 1px solid #e0e0e0; }}
+    th {{ background: #f5f5f5; font-weight: 600; }}
+    td.pass {{ color: #2d8a4e; font-weight: 600; }}
+    td.fail {{ color: #d32f2f; font-weight: 600; }}
+    td.pos {{ color: #2d8a4e; }}
+    td.neg {{ color: #d32f2f; }}
+    tfoot td {{ font-weight: 600; border-top: 2px solid #333; }}
+    .chart {{ text-align: center; margin: 20px 0; }}
+    .chart img {{ max-width: 100%; height: auto; border: 1px solid #e0e0e0; border-radius: 4px; }}
+    .task-detail {{ margin: 20px 0 30px; padding: 16px; background: #fafafa; border-radius: 6px; border: 1px solid #e8e8e8; }}
+    .task-detail h3 {{ margin-bottom: 12px; }}
+    .task-detail .cat {{ color: #888; font-weight: normal; }}
+    .task-detail .pass {{ color: #2d8a4e; font-size: 0.85rem; margin-left: 8px; }}
+    .task-detail .fail {{ color: #d32f2f; font-size: 0.85rem; margin-left: 8px; }}
+    .scores {{ width: auto; }}
+    .scores td:nth-child(n+2) {{ text-align: center; min-width: 50px; }}
+    .scores th:nth-child(n+2) {{ text-align: center; }}
+    .observations {{ margin-top: 12px; font-size: 0.85rem; color: #444; }}
+    .observations p {{ margin-bottom: 6px; }}
+</style>
+</head>
+<body>
+
+<h1>Lush vs Bash Benchmark Report</h1>
+<p class="meta">Model: {html.escape(model)} &middot; Latest run: {html.escape(timestamp)} &middot; Tasks: {len(results)}</p>
+
+<h2>Summary</h2>
+{summary_table}
+
+<h2>Questionnaire Scores</h2>
+<div class="chart"><img src="data:image/png;base64,{chart_questionnaire}" alt="Questionnaire comparison"></div>
+
+<h2>Agent Turns (Category A)</h2>
+<div class="chart"><img src="data:image/png;base64,{chart_turns}" alt="Turns comparison"></div>
+
+<h2>Score Difference Heatmap (Lush - Bash)</h2>
+<div class="chart"><img src="data:image/png;base64,{chart_heatmap}" alt="Score heatmap"></div>
+
+<h2>Per-Task Detail</h2>
+{detail_html}
+
+</body>
+</html>"""
+
+    output_path.parent.mkdir(parents=True, exist_ok=True)
+    output_path.write_text(page)

lush_bench/harness.py

@@ -0,0 +1,156 @@
+from __future__ import annotations
+
+import os
+import shutil
+import subprocess
+import tempfile
+import time
+from pathlib import Path
+
+from .config import Config
+from .models import RunOutput, Task, TestCase, TestResult
+
+# Minimal base env — keeps scripts deterministic
+BASE_ENV_KEYS = {"PATH", "HOME", "USER", "LANG", "TERM", "TMPDIR"}
+
+
+def _build_env(test_case: TestCase) -> dict[str, str]:
+    """Build a controlled environment: base host vars + test-specific vars."""
+    env = {k: v for k, v in os.environ.items() if k in BASE_ENV_KEYS}
+    env.update(test_case.env)
+    return env
+
+
+def run_script(
+    command: list[str],
+    script: Path,
+    stdin: str,
+    timeout: float,
+    cwd: Path,
+    env: dict[str, str],
+) -> RunOutput:
+    start = time.monotonic()
+    try:
+        result = subprocess.run(
+            [*command, str(script)],
+            input=stdin,
+            capture_output=True,
+            text=True,
+            timeout=timeout,
+            cwd=cwd,
+            env=env,
+        )
+        elapsed_ms = (time.monotonic() - start) * 1000
+        return RunOutput(
+            stdout=result.stdout,
+            stderr=result.stderr,
+            exit_code=result.returncode,
+            runtime_ms=elapsed_ms,
+        )
+    except subprocess.TimeoutExpired:
+        elapsed_ms = (time.monotonic() - start) * 1000
+        return RunOutput(
+            stdout="",
+            stderr="Timeout exceeded",
+            exit_code=-1,
+            runtime_ms=elapsed_ms,
+        )
+
+
+def normalize(s: str) -> str:
+    return s.strip()
+
+
+def _setup_sandbox(tc: TestCase) -> Path:
+    """Create a temp directory and populate it with setup files."""
+    sandbox = Path(tempfile.mkdtemp(prefix="lush_bench_"))
+    for filename, content in tc.setup_files.items():
+        filepath = sandbox / filename
+        filepath.parent.mkdir(parents=True, exist_ok=True)
+        filepath.write_text(content)
+    return sandbox
+
+
+def _check_expected_files(
+    sandbox: Path,
+    tc: TestCase,
+    do_normalize: bool,
+) -> dict[str, dict[str, str]]:
+    """Compare expected files against sandbox contents. Returns mismatches."""
+    mismatches: dict[str, dict[str, str]] = {}
+    for filename, expected_content in tc.expected_files.items():
+        filepath = sandbox / filename
+        if not filepath.exists():
+            mismatches[filename] = {
+                "expected": expected_content,
+                "actual": "<file not found>",
+            }
+            continue
+        actual_content = filepath.read_text()
+        expected = expected_content
+        actual = actual_content
+        if do_normalize:
+            expected = normalize(expected)
+            actual = normalize(actual)
+        if actual != expected:
+            mismatches[filename] = {
+                "expected": expected_content,
+                "actual": actual_content,
+            }
+    return mismatches
+
+
+def evaluate(
+    task: Task,
+    code: str,
+    language: str,
+    config: Config,
+) -> list[TestResult]:
+    suffix = ".sh" if language == "bash" else ".lua"
+    results: list[TestResult] = []
+
+    for i, tc in enumerate(task.test_cases):
+        sandbox = _setup_sandbox(tc)
+        try:
+            # Write script into the sandbox
+            script_path = sandbox / f"solution{suffix}"
+            script_path.write_text(code)
+
+            env = _build_env(tc)
+
+            if language == "bash":
+                command = ["bash"]
+            else:
+                command = [str(config.lush_binary)]
+
+            output = run_script(
+                command, script_path, tc.stdin, config.timeout_seconds, sandbox, env
+            )
+
+            actual = output.stdout
+            expected = tc.expected_stdout
+            if config.normalize_whitespace:
+                actual = normalize(actual)
+                expected = normalize(expected)
+
+            stdout_ok = actual == expected
+            file_mismatches = _check_expected_files(
+                sandbox, tc, config.normalize_whitespace
+            )
+            passed = stdout_ok and not file_mismatches
+
+            results.append(
+                TestResult(
+                    test_case_index=i,
+                    passed=passed,
+                    actual_stdout=output.stdout,
+                    expected_stdout=tc.expected_stdout,
+                    stderr=output.stderr,
+                    exit_code=output.exit_code,
+                    file_mismatches=file_mismatches,
+                )
+            )
+        finally:
+            shutil.rmtree(sandbox, ignore_errors=True)
+
+    return results

lush_bench/models.py

@@ -0,0 +1,210 @@
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Any
+
+
+@dataclass
+class TestCase:
+    stdin: str
+    expected_stdout: str
+    env: dict[str, str] = field(default_factory=dict)
+    setup_files: dict[str, str] = field(default_factory=dict)
+    expected_files: dict[str, str] = field(default_factory=dict)
+
+    def to_dict(self) -> dict[str, Any]:
+        d: dict[str, Any] = {"stdin": self.stdin, "expected_stdout": self.expected_stdout}
+        if self.env:
+            d["env"] = self.env
+        if self.setup_files:
+            d["setup_files"] = self.setup_files
+        if self.expected_files:
+            d["expected_files"] = self.expected_files
+        return d
+
+    @classmethod
+    def from_dict(cls, d: dict[str, Any]) -> TestCase:
+        return cls(
+            stdin=d["stdin"],
+            expected_stdout=d["expected_stdout"],
+            env=d.get("env", {}),
+            setup_files=d.get("setup_files", {}),
+            expected_files=d.get("expected_files", {}),
+        )
+
+
+@dataclass
+class Task:
+    name: str
+    category: str  # "a" or "b"
+    description: str
+    test_cases: list[TestCase]
+    bash_source: str | None = None  # category B only
+
+    def to_dict(self) -> dict[str, Any]:
+        d: dict[str, Any] = {
+            "name": self.name,
+            "category": self.category,
+            "description": self.description,
+            "test_cases": [tc.to_dict() for tc in self.test_cases],
+        }
+        if self.bash_source is not None:
+            d["bash_source"] = self.bash_source
+        return d
+
+    @classmethod
+    def from_dict(cls, d: dict[str, Any]) -> Task:
+        return cls(
+            name=d["name"],
+            category=d["category"],
+            description=d["description"],
+            test_cases=[TestCase.from_dict(tc) for tc in d["test_cases"]],
+            bash_source=d.get("bash_source"),
+        )
+
+
+@dataclass
+class RunOutput:
+    stdout: str
+    stderr: str
+    exit_code: int
+    runtime_ms: float
+
+    def to_dict(self) -> dict[str, Any]:
+        return {
+            "stdout": self.stdout,
+            "stderr": self.stderr,
+            "exit_code": self.exit_code,
+            "runtime_ms": self.runtime_ms,
+        }
+
+    @classmethod
+    def from_dict(cls, d: dict[str, Any]) -> RunOutput:
+        return cls(
+            stdout=d["stdout"],
+            stderr=d["stderr"],
+            exit_code=d["exit_code"],
+            runtime_ms=d["runtime_ms"],
+        )
+
+
+@dataclass
+class TestResult:
+    test_case_index: int
+    passed: bool
+    actual_stdout: str
+    expected_stdout: str
+    stderr: str
+    exit_code: int
+    file_mismatches: dict[str, dict[str, str]] = field(default_factory=dict)
+
+    def to_dict(self) -> dict[str, Any]:
+        d: dict[str, Any] = {
+            "test_case_index": self.test_case_index,
+            "passed": self.passed,
+            "actual_stdout": self.actual_stdout,
+            "expected_stdout": self.expected_stdout,
+            "stderr": self.stderr,
+            "exit_code": self.exit_code,
+        }
+        if self.file_mismatches:
+            d["file_mismatches"] = self.file_mismatches
+        return d
+
+    @classmethod
+    def from_dict(cls, d: dict[str, Any]) -> TestResult:
+        return cls(
+            test_case_index=d["test_case_index"],
+            passed=d["passed"],
+            actual_stdout=d["actual_stdout"],
+            expected_stdout=d["expected_stdout"],
+            stderr=d["stderr"],
+            exit_code=d["exit_code"],
+            file_mismatches=d.get("file_mismatches", {}),
+        )
+
+
+@dataclass
+class LanguageResult:
+    language: str
+    solution_code: str
+    test_results: list[TestResult]
+    all_passed: bool
+    agent_turns: int
+    questionnaire: list[QuestionnaireResponse] = field(default_factory=list)
+
+    def to_dict(self) -> dict[str, Any]:
+        return {
+            "language": self.language,
+            "solution_code": self.solution_code,
+            "test_results": [tr.to_dict() for tr in self.test_results],
+            "all_passed": self.all_passed,
+            "agent_turns": self.agent_turns,
+            "questionnaire": [q.to_dict() for q in self.questionnaire],
+        }
+
+    @classmethod
+    def from_dict(cls, d: dict[str, Any]) -> LanguageResult:
+        return cls(
+            language=d["language"],
+            solution_code=d["solution_code"],
+            test_results=[TestResult.from_dict(tr) for tr in d["test_results"]],
+            all_passed=d["all_passed"],
+            agent_turns=d["agent_turns"],
+            questionnaire=[QuestionnaireResponse.from_dict(q) for q in d.get("questionnaire", [])],
+        )
+
+
+@dataclass
+class QuestionnaireResponse:
+    question: str
+    selected: str | int
+    choices: list[str] | None = None
+
+    def to_dict(self) -> dict[str, Any]:
+        d: dict[str, Any] = {"question": self.question, "selected": self.selected}
+        if self.choices is not None:
+            d["choices"] = self.choices
+        return d
+
+    @classmethod
+    def from_dict(cls, d: dict[str, Any]) -> QuestionnaireResponse:
+        return cls(
+            question=d["question"],
+            selected=d["selected"],
+            choices=d.get("choices"),
+        )
+
+
+@dataclass
+class BenchmarkResult:
+    task_name: str
+    category: str
+    provider: str
+    model: str
+    timestamp: str
+    bash_result: LanguageResult | None
+    lush_result: LanguageResult | None
+
+    def to_dict(self) -> dict[str, Any]:
+        return {
+            "task_name": self.task_name,
+            "category": self.category,
+            "provider": self.provider,
+            "model": self.model,
+            "timestamp": self.timestamp,
+            "bash_result": self.bash_result.to_dict() if self.bash_result else None,
+            "lush_result": self.lush_result.to_dict() if self.lush_result else None,
+        }
+
+    @classmethod
+    def from_dict(cls, d: dict[str, Any]) -> BenchmarkResult:
+        return cls(
+            task_name=d["task_name"],
+            category=d["category"],
+            provider=d["provider"],
+            model=d["model"],
+            timestamp=d["timestamp"],
+            bash_result=LanguageResult.from_dict(d["bash_result"]) if d.get("bash_result") else None,
+            lush_result=LanguageResult.from_dict(d["lush_result"]) if d.get("lush_result") else None,
+        )

lush_bench/providers/anthropic.py

@@ -0,0 +1,35 @@
+from __future__ import annotations
+
+import os
+from typing import Any
+
+import anthropic
+
+from .base import Message
+
+
+class AnthropicProvider:
+    def __init__(self, config: dict[str, Any]) -> None:
+        api_key_env = config.get("api_key_env", "ANTHROPIC_API_KEY")
+        api_key = os.environ.get(api_key_env)
+        if not api_key:
+            raise RuntimeError(f"Set {api_key_env} environment variable")
+        self._client = anthropic.Anthropic(api_key=api_key)
+        self._model = config.get("model", "claude-sonnet-4-20250514")
+        self._max_tokens = config.get("max_tokens", 4096)
+
+    def send(self, messages: list[Message], system: str = "") -> str:
+        api_messages = [{"role": m.role, "content": m.content} for m in messages]
+        kwargs: dict[str, Any] = {
+            "model": self._model,
+            "max_tokens": self._max_tokens,
+            "messages": api_messages,
+        }
+        if system:
+            kwargs["system"] = system
+        response = self._client.messages.create(**kwargs)
+        return response.content[0].text
+
+    @property
+    def model_name(self) -> str:
+        return self._model

lush_bench/providers/base.py

@@ -0,0 +1,17 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Protocol
+
+
+@dataclass
+class Message:
+    role: str  # "user" or "assistant"
+    content: str
+
+
+class LLMProvider(Protocol):
+    def send(self, messages: list[Message], system: str = "") -> str: ...
+
+    @property
+    def model_name(self) -> str: ...

lush_bench/questionnaire.py

@@ -0,0 +1,91 @@
+from __future__ import annotations
+
+import json
+import re
+
+from .models import QuestionnaireResponse
+from .providers.base import LLMProvider, Message
+
+QUESTIONS = [
+    {
+        "question": "Readability: The solution is easy to read and understand",
+        "choices": ["1 - Strongly disagree", "2 - Disagree", "3 - Neutral", "4 - Agree", "5 - Strongly agree"],
+    },
+    {
+        "question": "Expressiveness: The language provided sufficient constructs to solve the problem naturally",
+        "choices": ["1 - Strongly disagree", "2 - Disagree", "3 - Neutral", "4 - Agree", "5 - Strongly agree"],
+    },
+    {
+        "question": "Conciseness: The solution required minimal boilerplate",
+        "choices": ["1 - Strongly disagree", "2 - Disagree", "3 - Neutral", "4 - Agree", "5 - Strongly agree"],
+    },
+    {
+        "question": "Error handling: Error handling was straightforward",
+        "choices": ["1 - Strongly disagree", "2 - Disagree", "3 - Neutral", "4 - Agree", "5 - Strongly agree"],
+    },
+    {
+        "question": "Overall preference: I would prefer this language for similar tasks",
+        "choices": ["1 - Strongly disagree", "2 - Disagree", "3 - Neutral", "4 - Agree", "5 - Strongly agree"],
+    },
+    {
+        "question": "Learning curve: An unfamiliar developer could understand the solution quickly",
+        "choices": ["1 - Strongly disagree", "2 - Disagree", "3 - Neutral", "4 - Agree", "5 - Strongly agree"],
+    },
+]
+
+
+def build_questionnaire_prompt(
+    task_name: str,
+    language: str,
+    solution_code: str,
+) -> str:
+    questions_text = ""
+    for i, q in enumerate(QUESTIONS, 1):
+        choices_str = ", ".join(f'"{c}"' for c in q["choices"])
+        questions_text += f'  {{"question": "{q["question"]}", "choices": [{choices_str}], "selected": <your choice>}},\n'
+
+    return f"""You just solved the task "{task_name}" in {language}. Here is your solution:
+
+```
+{solution_code}
+```
+
+Please evaluate your experience by answering the following questionnaire. Respond with ONLY a JSON array — no other text.
+
+[
+{questions_text}  {{"question": "Free-form observation about using {language} for this task", "selected": "<your observation>"}}
+]"""
+
+
+def parse_questionnaire_response(response: str) -> list[QuestionnaireResponse]:
+    # Try to extract JSON array from response
+    json_match = re.search(r"\[.*\]", response, re.DOTALL)
+    if not json_match:
+        return [QuestionnaireResponse(question="raw_response", selected=response)]
+
+    try:
+        data = json.loads(json_match.group())
+    except json.JSONDecodeError:
+        return [QuestionnaireResponse(question="raw_response", selected=response)]
+
+    results = []
+    for item in data:
+        results.append(
+            QuestionnaireResponse(
+                question=item.get("question", ""),
+                selected=item.get("selected", ""),
+                choices=item.get("choices"),
+            )
+        )
+    return results
+
+
+def run_questionnaire(
+    provider: LLMProvider,
+    task_name: str,
+    language: str,
+    solution_code: str,
+) -> list[QuestionnaireResponse]:
+    prompt = build_questionnaire_prompt(task_name, language, solution_code)
+    response = provider.send([Message(role="user", content=prompt)])
+    return parse_questionnaire_response(response)

lush_bench/report.py

@@ -0,0 +1,228 @@
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+from .models import BenchmarkResult
+
+# Likert questions in order (must match questionnaire.py QUESTIONS)
+LIKERT_QUESTIONS = [
+    ("Readability", "Readability"),
+    ("Expressiveness", "Expressiveness"),
+    ("Conciseness", "Conciseness"),
+    ("Error handling", "Error handling"),
+    ("Overall preference", "Overall preference"),
+    ("Learning curve", "Learning curve"),
+]
+
+
+def load_latest_results(results_dir: Path) -> list[BenchmarkResult]:
+    """Load results, keeping only the latest run per task name."""
+    latest: dict[str, BenchmarkResult] = {}
+    for d in sorted(results_dir.iterdir()):
+        result_file = d / "result.json"
+        if not result_file.exists():
+            continue
+        with open(result_file) as f:
+            r = BenchmarkResult.from_dict(json.load(f))
+        latest[r.task_name] = r
+    return sorted(latest.values(), key=lambda r: (r.category, r.task_name))
+
+
+def _parse_likert(selected: str | int) -> int | None:
+    """Extract numeric value from a likert response like '4 - Agree'."""
+    if isinstance(selected, int):
+        return selected
+    s = str(selected).strip()
+    if s and s[0].isdigit():
+        return int(s[0])
+    return None
+
+
+def _get_likert_scores(result: BenchmarkResult) -> dict[str, dict[str, float | None]]:
+    """Extract likert scores per language. Returns {question_key: {bash: N, lush: N}}."""
+    scores: dict[str, dict[str, float | None]] = {}
+    for key, _ in LIKERT_QUESTIONS:
+        scores[key] = {"bash": None, "lush": None}
+
+    for lang_name, lang_result in [("bash", result.bash_result), ("lush", result.lush_result)]:
+        if not lang_result:
+            continue
+        for q in lang_result.questionnaire:
+            for key, _ in LIKERT_QUESTIONS:
+                if q.question.startswith(key):
+                    val = _parse_likert(q.selected)
+                    if val is not None:
+                        scores[key][lang_name] = float(val)
+                    break
+    return scores
+
+
+def _bar(value: float, max_val: float = 5.0, width: int = 20) -> str:
+    """Render a small horizontal bar."""
+    filled = int(round(value / max_val * width))
+    return "\u2588" * filled + "\u2591" * (width - filled)
+
+
+def _get_freeform(result: BenchmarkResult) -> dict[str, str]:
+    """Extract free-form observations per language."""
+    obs: dict[str, str] = {}
+    for lang_name, lang_result in [("bash", result.bash_result), ("lush", result.lush_result)]:
+        if not lang_result:
+            continue
+        for q in lang_result.questionnaire:
+            if q.question.startswith("Free-form"):
+                obs[lang_name] = str(q.selected)
+                break
+    return obs
+
+
+def render_summary_table(results: list[BenchmarkResult]) -> str:
+    """Render the pass/fail + turns overview table."""
+    lines: list[str] = []
+    lines.append("")
+    lines.append("=" * 78)
+    lines.append("  BENCHMARK RESULTS SUMMARY")
+    lines.append("=" * 78)
+    lines.append("")
+
+    header = f"  {'Task':<22s} {'Cat':>3s}  {'Bash':^14s}  {'Lush':^14s}"
+    lines.append(header)
+    sub = f"  {'':<22s} {'':>3s}  {'pass  turns':^14s}  {'pass  turns':^14s}"
+    lines.append(sub)
+    lines.append("  " + "-" * 60)
+
+    for r in results:
+        b = r.bash_result
+        l = r.lush_result
+        b_pass = "PASS" if b and b.all_passed else "FAIL" if b else "-"
+        l_pass = "PASS" if l and l.all_passed else "FAIL" if l else "-"
+        b_turns = str(b.agent_turns) if b else "-"
+        l_turns = str(l.agent_turns) if l else "-"
+        lines.append(f"  {r.task_name:<22s} [{r.category}]  {b_pass:>4s}  {b_turns:>5s}     {l_pass:>4s}  {l_turns:>5s}")
+
+    # Totals
+    b_passed = sum(1 for r in results if r.bash_result and r.bash_result.all_passed)
+    l_passed = sum(1 for r in results if r.lush_result and r.lush_result.all_passed)
+    b_total = sum(1 for r in results if r.bash_result)
+    l_total = sum(1 for r in results if r.lush_result)
+    b_turns_avg = 0.0
+    l_turns_avg = 0.0
+    b_turn_counts = [r.bash_result.agent_turns for r in results if r.bash_result and r.bash_result.agent_turns > 0]
+    l_turn_counts = [r.lush_result.agent_turns for r in results if r.lush_result and r.lush_result.agent_turns > 0]
+    if b_turn_counts:
+        b_turns_avg = sum(b_turn_counts) / len(b_turn_counts)
+    if l_turn_counts:
+        l_turns_avg = sum(l_turn_counts) / len(l_turn_counts)
+
+    lines.append("  " + "-" * 60)
+    lines.append(f"  {'TOTAL':<22s}      {b_passed}/{b_total:>2d}  {b_turns_avg:>5.1f}     {l_passed}/{l_total:>2d}  {l_turns_avg:>5.1f}")
+    lines.append(f"  {'':27s}{'pass  avg turns':^14s}  {'pass  avg turns':^14s}")
+    lines.append("")
+    return "\n".join(lines)
+
+
+def render_questionnaire_comparison(results: list[BenchmarkResult]) -> str:
+    """Render aggregated questionnaire scores with bar charts."""
+    lines: list[str] = []
+    lines.append("=" * 78)
+    lines.append("  QUESTIONNAIRE SCORES (1-5 Likert, higher = better)")
+    lines.append("=" * 78)
+    lines.append("")
+
+    # Aggregate scores across all tasks
+    agg: dict[str, dict[str, list[float]]] = {}
+    for key, _ in LIKERT_QUESTIONS:
+        agg[key] = {"bash": [], "lush": []}
+
+    for r in results:
+        scores = _get_likert_scores(r)
+        for key in scores:
+            for lang in ("bash", "lush"):
+                val = scores[key][lang]
+                if val is not None:
+                    agg[key][lang].append(val)
+
+    for key, label in LIKERT_QUESTIONS:
+        b_vals = agg[key]["bash"]
+        l_vals = agg[key]["lush"]
+        b_avg = sum(b_vals) / len(b_vals) if b_vals else 0.0
+        l_avg = sum(l_vals) / len(l_vals) if l_vals else 0.0
+        diff = l_avg - b_avg
+        diff_str = f"+{diff:.1f}" if diff > 0 else f"{diff:.1f}" if diff < 0 else " 0.0"
+
+        lines.append(f"  {label}")
+        lines.append(f"    bash  {_bar(b_avg)} {b_avg:.1f}")
+        lines.append(f"    lush  {_bar(l_avg)} {l_avg:.1f}  ({diff_str})")
+        lines.append("")
+
+    # Overall average
+    all_bash = [v for key in agg for v in agg[key]["bash"]]
+    all_lush = [v for key in agg for v in agg[key]["lush"]]
+    b_overall = sum(all_bash) / len(all_bash) if all_bash else 0.0
+    l_overall = sum(all_lush) / len(all_lush) if all_lush else 0.0
+    diff = l_overall - b_overall
+    diff_str = f"+{diff:.1f}" if diff > 0 else f"{diff:.1f}" if diff < 0 else " 0.0"
+
+    lines.append("  " + "-" * 50)
+    lines.append(f"  Overall average")
+    lines.append(f"    bash  {_bar(b_overall)} {b_overall:.1f}")
+    lines.append(f"    lush  {_bar(l_overall)} {l_overall:.1f}  ({diff_str})")
+    lines.append("")
+    return "\n".join(lines)
+
+
+def render_per_task_detail(results: list[BenchmarkResult]) -> str:
+    """Render per-task questionnaire breakdown."""
+    lines: list[str] = []
+    lines.append("=" * 78)
+    lines.append("  PER-TASK DETAIL")
+    lines.append("=" * 78)
+
+    for r in results:
+        lines.append("")
+        b_status = "PASS" if r.bash_result and r.bash_result.all_passed else "FAIL"
+        l_status = "PASS" if r.lush_result and r.lush_result.all_passed else "FAIL"
+        lines.append(f"  {r.task_name} [{r.category}]  bash={b_status}  lush={l_status}")
+        lines.append("")
+
+        scores = _get_likert_scores(r)
+        lines.append(f"    {'Metric':<22s} {'Bash':>4s}  {'Lush':>4s}  {'Diff':>5s}")
+        lines.append("    " + "-" * 40)
+        for key, label in LIKERT_QUESTIONS:
+            b_val = scores[key]["bash"]
+            l_val = scores[key]["lush"]
+            b_str = f"{b_val:.0f}" if b_val is not None else "-"
+            l_str = f"{l_val:.0f}" if l_val is not None else "-"
+            if b_val is not None and l_val is not None:
+                d = l_val - b_val
+                d_str = f"+{d:.0f}" if d > 0 else f"{d:.0f}" if d < 0 else "0"
+            else:
+                d_str = "-"
+            lines.append(f"    {label:<22s} {b_str:>4s}  {l_str:>4s}  {d_str:>5s}")
+
+        # Free-form observations
+        obs = _get_freeform(r)
+        if obs:
+            lines.append("")
+            for lang, text in obs.items():
+                # Wrap long text
+                wrapped = text[:120] + ("..." if len(text) > 120 else "")
+                lines.append(f"    {lang}: {wrapped}")
+
+    lines.append("")
+    return "\n".join(lines)
+
+
+def render_report(results_dir: Path) -> str:
+    """Generate full report."""
+    results = load_latest_results(results_dir)
+    if not results:
+        return "No results found."
+
+    parts = [
+        render_summary_table(results),
+        render_questionnaire_comparison(results),
+        render_per_task_detail(results),
+    ]
+    return "\n".join(parts)

lush_bench/results.py

@@ -0,0 +1,29 @@
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+from .models import BenchmarkResult
+
+
+def save_result(result: BenchmarkResult, output_dir: Path) -> Path:
+    dir_name = f"{result.timestamp}_{result.task_name}_{result.provider}"
+    result_dir = output_dir / dir_name
+    result_dir.mkdir(parents=True, exist_ok=True)
+
+    # Save JSON
+    with open(result_dir / "result.json", "w") as f:
+        json.dump(result.to_dict(), f, indent=2)
+
+    # Save solution files
+    if result.bash_result and result.bash_result.solution_code:
+        (result_dir / "solution.sh").write_text(result.bash_result.solution_code)
+    if result.lush_result and result.lush_result.solution_code:
+        (result_dir / "solution.lua").write_text(result.lush_result.solution_code)
+
+    return result_dir
+
+
+def load_result(path: Path) -> BenchmarkResult:
+    with open(path / "result.json") as f:
+        return BenchmarkResult.from_dict(json.load(f))

lush_reference.md

@@ -0,0 +1,246 @@
+# Lush
+
+Lush is a shell built on [Lua 5.5.0](https://www.lua.org/). It extends Lua with shell-oriented features — backtick commands, pipes, globbing, interpolation, environment variables — while remaining a fully compatible Lua 5.5 interpreter.
+
+Based on [Lua](https://www.lua.org/) by R. Ierusalimschy, L. H. de Figueiredo, W. Celes (PUC-Rio).
+
+## Quick Start
+
+Build and run:
+
+```sh
+make
+./lush
+```
+
+## Language Guide
+
+Lush is Lua with shell extensions. Every valid Lua program runs unchanged. The additions are described below.
+
+### Backtick Commands
+
+Execute shell commands with backticks. Each command runs in its own child process. Stdout and stderr are captured and returned as a table with `code`, `stdout`, and `stderr` fields.
+
+```lua
+local r = `echo hello`
+print(r.stdout)   -- "hello\n"
+print(r.code)     -- 0
+
+local r = `ls nonexistent`
+print(r.code)     -- non-zero
+print(r.stderr)   -- error message
+```
+
+Empty backticks return `{code=0, stdout="", stderr=""}`. A command killed by a signal returns exit code 128 + signal number (e.g. 137 for SIGKILL).
+
+### Interactive Commands
+
+Prefix a line with `!` to run a command in a child process with stdout and stderr inherited from the terminal. The result is stored in `_`.
+
+```lua
+!ls -la
+print(_.code)   -- 0
+
+!sh -c "exit 42"
+print(_.code)   -- 42
+```
+
+Works anywhere a statement is valid — inside functions, loops, if-blocks.
+
+### Pipes
+
+Use `|` to connect commands in a pipeline. Each stage runs in its own process with stdout piped to the next stage's stdin.
+
+```lua
+local r = `echo hello | tr a-z A-Z`
+print(r.stdout)   -- "HELLO\n"
+
+!ps aux | grep lush | head -5
+```
+
+The exit code comes from the last stage. Stderr from the last stage is captured (in backtick mode); stderr from middle stages goes to the terminal. Quoting (`"a|b"`, `'a|b'`, `a\|b`) treats `|` as literal.
+
+### String Interpolation
+
+Three forms of interpolation inside backtick and interactive commands:
+
+`**${expr}` — Lua expression:**
+
+```lua
+local name = "world"
+`echo ${name}`              -- hello world
+`echo ${40 + 2}`            -- 42
+`echo ${name:upper()}`      -- WORLD
+```
+
+`**$NAME` — Environment variable:**
+
+```lua
+`echo $HOME`
+`echo $USER`
+```
+
+`**$(cmd)` — Subcommand substitution:**
+
+```lua
+`echo today is $(date +%Y-%m-%d)`
+`echo $(echo $(echo nested))`      -- nested substitution
+```
+
+Escape with backslash: `\$HOME` produces the literal string `$HOME`.
+
+### Environment Variables
+
+Read and write environment variables directly from Lua using `$NAME` syntax:
+
+```lua
+-- Read
+local home = $HOME
+local path = $PATH
+
+-- Write (visible to child processes)
+$MY_VAR = "hello"
+`echo $MY_VAR`          -- hello
+
+-- Unset
+$MY_VAR = nil
+
+-- Numbers are coerced to strings
+$PORT = 8080
+```
+
+### Globbing
+
+Shell glob patterns are expanded inside backtick commands:
+
+```lua
+`echo *.lua`                -- expands to matching files
+`echo src/**/*.c`
+`echo file?.txt`            -- single-character wildcard
+`echo config.[ch]`          -- bracket patterns
+```
+
+Brace expansion:
+
+```lua
+`echo {a,b,c}`             -- a b c
+`echo file.{lua,c,h}`      -- file.lua file.c file.h
+```
+
+Tilde expansion:
+
+```lua
+`echo ~`                    -- /home/user
+`echo ~/projects`           -- /home/user/projects
+```
+
+Quoting suppresses expansion: `"*.lua"`, `'*.lua'`, and `\*.lua` are all literal.
+
+### Quoting
+
+Single quotes are literal (no escapes):
+
+```lua
+`echo 'hello world'`
+`echo 'no $expansion here'`
+```
+
+Double quotes allow escapes and interpolation:
+
+```lua
+`echo "hello world"`
+`echo "tab:\there"`
+`echo "path is $HOME"`
+`echo "sum is ${1 + 2}"`
+```
+
+Backslash outside quotes escapes the next character:
+
+```lua
+`echo hello\ world`        -- single argument: hello world
+```
+
+### Builtins
+
+Built-in commands that affect the shell process:
+
+```lua
+`cd /tmp`                   -- change directory
+`cd -`                      -- previous directory
+`cd`                        -- home directory
+
+`umask`                     -- query current umask
+`umask 0077`                -- set umask
+```
+
+### The `lush` Library
+
+Programmatic API for shell operations:
+
+```lua
+lush.capture("echo hello")        -- like backticks, returns {code, stdout, stderr}
+lush.run("echo hello")            -- returns stdout with trailing newline stripped
+lush.interactive("ls")            -- like !, returns result and sets _
+
+lush.envget("HOME")               -- read env var
+lush.envset("MY_VAR", "value")    -- write env var
+```
+
+### Extensibility
+
+**Custom commands** run in a child process (like any external command), so their output is captured and they support piping:
+
+```lua
+lush.commands.greet = function(name, ...)
+  print("hello " .. (({...})[1] or "world"))
+end
+
+`greet lush`                -- hello lush
+`greet lush | tr a-z A-Z`  -- HELLO LUSH
+```
+
+**Custom builtins** run in the current Lua process, so they can modify shell state (like `cd` does). They receive the raw command table and return a result table:
+
+```lua
+lush.builtins.hello = function(cmd, name)
+  return {code = 0, stdout = "hi " .. (name or "") .. "\n", stderr = ""}
+end
+
+`hello world`               -- hi world
+```
+
+**Aliases:**
+
+```lua
+lush.aliases.ll = "ls -la"
+`ll`                         -- runs: ls -la
+
+lush.aliases.ll = nil        -- remove alias
+```
+
+### Configuration
+
+Lush loads config files on interactive startup (suppressed with `-E`):
+
+- `$XDG_CONFIG_HOME/lush/config.lua` — main config
+- `$XDG_CONFIG_HOME/lush/config.d/*.lua` — additional configs, loaded alphabetically
+
+Use config files to set up aliases, custom commands, prompts, and environment.
+
+### Prompt
+
+Customize the interactive prompt:
+
+```lua
+-- In config.lua:
+_PROMPT = "lush> "
+_PROMPT2 = "...> "
+
+-- Dynamic prompt:
+_PROMPT = setmetatable({}, {
+  __tostring = function()
+    return os.date("%H:%M") .. " > "
+  end
+})
+```
+

main.py

@@ -0,0 +1,198 @@
+from __future__ import annotations
+
+import argparse
+import sys
+import tomllib
+from datetime import datetime, timezone
+from pathlib import Path
+
+from lush_bench.agent import solve_task
+from lush_bench.config import Config
+from lush_bench.harness import evaluate
+from lush_bench.models import BenchmarkResult, LanguageResult, Task, TestCase
+from lush_bench.providers.anthropic import AnthropicProvider
+from lush_bench.questionnaire import run_questionnaire
+from lush_bench.export import export_html
+from lush_bench.report import render_report
+from lush_bench.results import save_result
+
+
+PROVIDERS = {
+    "anthropic": AnthropicProvider,
+}
+
+
+def load_task(path: Path) -> Task:
+    raw = tomllib.loads(path.read_text())
+    test_cases = [
+        TestCase(
+            stdin=tc.get("stdin", ""),
+            expected_stdout=tc.get("expected_stdout", ""),
+            env=tc.get("env", {}),
+            setup_files=tc.get("setup_files", {}),
+            expected_files=tc.get("expected_files", {}),
+        )
+        for tc in raw["test_cases"]
+    ]
+    return Task(
+        name=raw["name"],
+        category=raw["category"],
+        description=raw["description"],
+        test_cases=test_cases,
+        bash_source=raw.get("bash_source"),
+    )
+
+
+def find_tasks(category: str | None = None) -> list[Path]:
+    tasks_dir = Path(__file__).parent / "tasks"
+    paths = []
+    if category:
+        cat_dir = tasks_dir / f"category_{category}"
+        if cat_dir.exists():
+            paths = sorted(cat_dir.glob("*.toml"))
+    else:
+        for cat_dir in sorted(tasks_dir.iterdir()):
+            if cat_dir.is_dir():
+                paths.extend(sorted(cat_dir.glob("*.toml")))
+    return paths
+
+
+def cmd_list_tasks(args: argparse.Namespace) -> None:
+    paths = find_tasks(args.category)
+    if not paths:
+        print("No tasks found.")
+        return
+    for p in paths:
+        task = load_task(p)
+        print(f"  [{task.category}] {task.name:20s}  {p.relative_to(Path.cwd())}")
+
+
+def cmd_run(args: argparse.Namespace) -> None:
+    config = Config.load()
+    task_path = Path(args.task)
+    task = load_task(task_path)
+
+    provider_name = args.provider
+    if provider_name not in PROVIDERS:
+        print(f"Unknown provider: {provider_name}. Available: {', '.join(PROVIDERS)}")
+        sys.exit(1)
+
+    provider_config = config.provider_configs.get(provider_name, {})
+    provider = PROVIDERS[provider_name](provider_config)
+    timestamp = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%SZ")
+
+    print(f"Running task: {task.name} (category {task.category}) with {provider.model_name}")
+
+    bash_result = None
+    lush_result = None
+
+    if task.category == "a":
+        # Category A: solve in both languages
+        print("  Solving in bash...")
+        bash_result = solve_task(provider, task, "bash", config)
+        print(f"  Bash: {'PASS' if bash_result.all_passed else 'FAIL'} ({bash_result.agent_turns} turns)")
+
+        print("  Solving in lush...")
+        lush_result = solve_task(provider, task, "lush", config)
+        print(f"  Lush: {'PASS' if lush_result.all_passed else 'FAIL'} ({lush_result.agent_turns} turns)")
+
+    elif task.category == "b":
+        # Category B: verify provided bash source directly, then convert to lush
+        assert task.bash_source, f"Category B task {task.name} missing bash_source"
+        print("  Verifying provided bash source...")
+        test_results = evaluate(task, task.bash_source, "bash", config)
+        all_passed = all(tr.passed for tr in test_results)
+        bash_result = LanguageResult(
+            language="bash",
+            solution_code=task.bash_source,
+            test_results=test_results,
+            all_passed=all_passed,
+            agent_turns=0,
+        )
+        print(f"  Bash: {'PASS' if all_passed else 'FAIL'}")
+
+        print("  Converting to lush...")
+        lush_result = solve_task(provider, task, "lush", config)
+        print(f"  Lush: {'PASS' if lush_result.all_passed else 'FAIL'} ({lush_result.agent_turns} turns)")
+
+    # Run questionnaire for each completed language
+    for lang, result in [("bash", bash_result), ("lush", lush_result)]:
+        if result and result.solution_code:
+            print(f"  Questionnaire for {lang}...")
+            result.questionnaire = run_questionnaire(provider, task.name, lang, result.solution_code)
+
+    benchmark = BenchmarkResult(
+        task_name=task.name,
+        category=task.category,
+        provider=provider_name,
+        model=provider.model_name,
+        timestamp=timestamp,
+        bash_result=bash_result,
+        lush_result=lush_result,
+    )
+
+    result_dir = save_result(benchmark, config.output_dir)
+    print(f"  Results saved to {result_dir}")
+
+
+def cmd_run_all(args: argparse.Namespace) -> None:
+    paths = find_tasks(args.category)
+    if not paths:
+        print("No tasks found.")
+        return
+
+    for p in paths:
+        # Reuse cmd_run by constructing a namespace
+        run_args = argparse.Namespace(task=str(p), provider=args.provider)
+        cmd_run(run_args)
+        print()
+
+
+def cmd_report(args: argparse.Namespace) -> None:
+    print(render_report(Path(args.results_dir)))
+
+
+def cmd_export(args: argparse.Namespace) -> None:
+    output = Path(args.output)
+    export_html(Path(args.results_dir), output)
+    print(f"Report exported to {output}")
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Lush vs Bash AI Benchmarking")
+    sub = parser.add_subparsers(dest="command", required=True)
+
+    # list-tasks
+    ls = sub.add_parser("list-tasks", help="List available tasks")
+    ls.add_argument("--category", choices=["a", "b"], help="Filter by category")
+    ls.set_defaults(func=cmd_list_tasks)
+
+    # run
+    run = sub.add_parser("run", help="Run a single task")
+    run.add_argument("--task", required=True, help="Path to task TOML file")
+    run.add_argument("--provider", default="anthropic", help="LLM provider")
+    run.set_defaults(func=cmd_run)
+
+    # run-all
+    ra = sub.add_parser("run-all", help="Run all tasks in a category")
+    ra.add_argument("--category", choices=["a", "b"], help="Category to run")
+    ra.add_argument("--provider", default="anthropic", help="LLM provider")
+    ra.set_defaults(func=cmd_run_all)
+
+    # report
+    rpt = sub.add_parser("report", help="Show results report in terminal")
+    rpt.add_argument("--results-dir", default="results", help="Results directory")
+    rpt.set_defaults(func=cmd_report)
+
+    # export
+    exp = sub.add_parser("export", help="Export HTML report with charts")
+    exp.add_argument("--results-dir", default="results", help="Results directory")
+    exp.add_argument("--output", "-o", default="report.html", help="Output HTML file")
+    exp.set_defaults(func=cmd_export)
+
+    args = parser.parse_args()
+    args.func(args)
+
+
+if __name__ == "__main__":
+    main()

pyproject.toml

@@ -0,0 +1,7 @@
+[project]
+name = "lush-benchmarking"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = ["anthropic>=0.40.0", "matplotlib>=3.8.0"]

report.html

@@ -0,0 +1,285 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="utf-8">
+<title>Lush vs Bash Benchmark Report</title>
+<style>
+    :root { --bash: #4E79A7; --lush: #E15759; }
+    * { box-sizing: border-box; margin: 0; padding: 0; }
+    body { font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, sans-serif;
+           max-width: 960px; margin: 40px auto; padding: 0 20px; color: #1a1a1a; line-height: 1.5; }
+    h1 { font-size: 1.8rem; margin-bottom: 4px; }
+    h2 { font-size: 1.3rem; margin: 32px 0 16px; border-bottom: 2px solid #e0e0e0; padding-bottom: 6px; }
+    h3 { font-size: 1.05rem; margin-bottom: 10px; }
+    .meta { color: #666; font-size: 0.9rem; margin-bottom: 24px; }
+    table { border-collapse: collapse; width: 100%; margin: 12px 0 20px; font-size: 0.9rem; }
+    th, td { padding: 8px 12px; text-align: left; border-bottom: 1px solid #e0e0e0; }
+    th { background: #f5f5f5; font-weight: 600; }
+    td.pass { color: #2d8a4e; font-weight: 600; }
+    td.fail { color: #d32f2f; font-weight: 600; }
+    td.pos { color: #2d8a4e; }
+    td.neg { color: #d32f2f; }
+    tfoot td { font-weight: 600; border-top: 2px solid #333; }
+    .chart { text-align: center; margin: 20px 0; }
+    .chart img { max-width: 100%; height: auto; border: 1px solid #e0e0e0; border-radius: 4px; }
+    .task-detail { margin: 20px 0 30px; padding: 16px; background: #fafafa; border-radius: 6px; border: 1px solid #e8e8e8; }
+    .task-detail h3 { margin-bottom: 12px; }
+    .task-detail .cat { color: #888; font-weight: normal; }
+    .task-detail .pass { color: #2d8a4e; font-size: 0.85rem; margin-left: 8px; }
+    .task-detail .fail { color: #d32f2f; font-size: 0.85rem; margin-left: 8px; }
+    .scores { width: auto; }
+    .scores td:nth-child(n+2) { text-align: center; min-width: 50px; }
+    .scores th:nth-child(n+2) { text-align: center; }
+    .observations { margin-top: 12px; font-size: 0.85rem; color: #444; }
+    .observations p { margin-bottom: 6px; }
+</style>
+</head>
+<body>
+
+<h1>Lush vs Bash Benchmark Report</h1>
+<p class="meta">Model: claude-sonnet-4-20250514 &middot; Latest run: 20260327T224550Z &middot; Tasks: 12</p>
+
+<h2>Summary</h2>
+<table>
+        <thead><tr>
+            <th>Task</th><th>Cat</th>
+            <th>Bash</th><th>Turns</th>
+            <th>Lush</th><th>Turns</th>
+        </tr></thead>
+        <tbody><tr>
+            <td>env_config</td><td>A</td>
+            <td class="pass">PASS</td><td>3</td>
+            <td class="pass">PASS</td><td>2</td>
+        </tr><tr>
+            <td>file_organizer</td><td>A</td>
+            <td class="fail">FAIL</td><td>4</td>
+            <td class="pass">PASS</td><td>1</td>
+        </tr><tr>
+            <td>fizzbuzz</td><td>A</td>
+            <td class="pass">PASS</td><td>1</td>
+            <td class="pass">PASS</td><td>1</td>
+        </tr><tr>
+            <td>multi_file_search</td><td>A</td>
+            <td class="pass">PASS</td><td>1</td>
+            <td class="pass">PASS</td><td>3</td>
+        </tr><tr>
+            <td>pipeline_transform</td><td>A</td>
+            <td class="pass">PASS</td><td>1</td>
+            <td class="pass">PASS</td><td>2</td>
+        </tr><tr>
+            <td>process_exit_codes</td><td>A</td>
+            <td class="pass">PASS</td><td>3</td>
+            <td class="pass">PASS</td><td>1</td>
+        </tr><tr>
+            <td>reverse_string</td><td>A</td>
+            <td class="pass">PASS</td><td>1</td>
+            <td class="pass">PASS</td><td>1</td>
+        </tr><tr>
+            <td>two_sum</td><td>A</td>
+            <td class="pass">PASS</td><td>1</td>
+            <td class="pass">PASS</td><td>1</td>
+        </tr><tr>
+            <td>csv_transform</td><td>B</td>
+            <td class="pass">PASS</td><td>0</td>
+            <td class="pass">PASS</td><td>1</td>
+        </tr><tr>
+            <td>env_path_builder</td><td>B</td>
+            <td class="pass">PASS</td><td>0</td>
+            <td class="pass">PASS</td><td>1</td>
+        </tr><tr>
+            <td>log_parser</td><td>B</td>
+            <td class="pass">PASS</td><td>0</td>
+            <td class="pass">PASS</td><td>1</td>
+        </tr><tr>
+            <td>pipeline_word_freq</td><td>B</td>
+            <td class="pass">PASS</td><td>0</td>
+            <td class="pass">PASS</td><td>1</td>
+        </tr></tbody>
+        <tfoot><tr>
+            <td><strong>Total</strong></td><td></td>
+            <td><strong>11/12</strong></td><td></td>
+            <td><strong>12/12</strong></td><td></td>
+        </tr></tfoot>
+    </table>
+
+<h2>Questionnaire Scores</h2>
+<div class="chart"><img src="data:image/png;base64,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 truncated
+
+<h2>Agent Turns (Category A)</h2>
+<div class="chart"><img src="data:image/png;base64,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 truncated
+
+<h2>Score Difference Heatmap (Lush - Bash)</h2>
+<div class="chart"><img src="data:image/png;base64,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 truncated
+
+<h2>Per-Task Detail</h2>
+
+        <div class="task-detail">
+            <h3>env_config <span class="cat">[a]</span>
+                <span class="pass">bash=PASS</span>
+                <span class="pass">lush=PASS</span>
+            </h3>
+            <table class="scores">
+                <thead><tr><th>Metric</th><th>Bash</th><th>Lush</th><th>Diff</th></tr></thead>
+                <tbody><tr><td>Readability</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Expressiveness</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Conciseness</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Error handling</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Overall preference</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Learning curve</td><td>2</td><td>4</td><td class="pos">+2</td></tr></tbody>
+            </table>
+            <div class="observations"><p><strong>bash:</strong> Bash&#x27;s regex matching and array handling work well for this task, but the syntax is arcane (${!key} for indirect variable access, BASH_REMATCH array). The printf-pipe-sort pattern for array sorting is a common bash idiom but not intuitive. Error handling would require additional validation that bash doesn&#x27;t make easy. Good for system administration contexts where bash is expected, but the syntax barriers make it less accessible than higher-level languages.</p>
+<p><strong>lush:</strong> Lush combines Lua&#x27;s familiarity with shell-like conveniences effectively. The backtick syntax for command execution and built-in functions like lush.envset feel natural. However, the solution required more manual string processing than ideal - having to parse env output and match keys could be more elegant with better built-in environment variable introspection.</p>
+</div>
+        </div>
+
+        <div class="task-detail">
+            <h3>file_organizer <span class="cat">[a]</span>
+                <span class="fail">bash=FAIL</span>
+                <span class="pass">lush=PASS</span>
+            </h3>
+            <table class="scores">
+                <thead><tr><th>Metric</th><th>Bash</th><th>Lush</th><th>Diff</th></tr></thead>
+                <tbody><tr><td>Readability</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Expressiveness</td><td>2</td><td>5</td><td class="pos">+3</td></tr><tr><td>Conciseness</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Error handling</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Overall preference</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Learning curve</td><td>2</td><td>4</td><td class="pos">+2</td></tr></tbody>
+            </table>
+            <div class="observations"><p><strong>bash:</strong> Bash required several workarounds and awkward constructs: dynamic variable creation with eval (security risk), manual string building for output sorting, complex parameter expansion syntax, and careful escaping. While bash excels at file operations, the lack of proper data structures made this solution verbose and harder to maintain compared to higher-level languages.</p>
+<p><strong>lush:</strong> Lush&#x27;s shell command interpolation with backticks and the seamless integration with Lua made this file organization task very natural to implement. The ability to execute shell commands inline while maintaining full Lua data structures for processing was particularly elegant for this type of system administration task.</p>
+</div>
+        </div>
+
+        <div class="task-detail">
+            <h3>fizzbuzz <span class="cat">[a]</span>
+                <span class="pass">bash=PASS</span>
+                <span class="pass">lush=PASS</span>
+            </h3>
+            <table class="scores">
+                <thead><tr><th>Metric</th><th>Bash</th><th>Lush</th><th>Diff</th></tr></thead>
+                <tbody><tr><td>Readability</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Expressiveness</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Conciseness</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Error handling</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Overall preference</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Learning curve</td><td>3</td><td>5</td><td class="pos">+2</td></tr></tbody>
+            </table>
+            <div class="observations"><p><strong>bash:</strong> Bash works well for FizzBuzz with clean arithmetic operations and conditionals. The C-style for loop syntax is familiar, but bash&#x27;s quirky syntax like double parentheses for arithmetic might confuse newcomers. Error handling for invalid input would require additional validation that bash doesn&#x27;t make particularly elegant.</p>
+<p><strong>lush:</strong> Lush&#x27;s Lua-like syntax made the FizzBuzz implementation very straightforward and clean. The language offers excellent readability with familiar control structures and operators. The modulo operator, conditional statements, and print function work exactly as expected, requiring no special syntax or workarounds.</p>
+</div>
+        </div>
+
+        <div class="task-detail">
+            <h3>multi_file_search <span class="cat">[a]</span>
+                <span class="pass">bash=PASS</span>
+                <span class="pass">lush=PASS</span>
+            </h3>
+            <table class="scores">
+                <thead><tr><th>Metric</th><th>Bash</th><th>Lush</th><th>Diff</th></tr></thead>
+                <tbody><tr><td>Readability</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Expressiveness</td><td>5</td><td>4</td><td class="neg">-1</td></tr><tr><td>Conciseness</td><td>5</td><td>3</td><td class="neg">-2</td></tr><tr><td>Error handling</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Overall preference</td><td>5</td><td>4</td><td class="neg">-1</td></tr><tr><td>Learning curve</td><td>3</td><td>3</td><td class="">0</td></tr></tbody>
+            </table>
+            <div class="observations"><p><strong>bash:</strong> Bash excels at text processing and file operations like this. The pipeline approach with grep, sed, and sort feels very natural. However, the syntax can be cryptic for newcomers (especially the sort flags), and proper error handling would require additional complexity that might hurt readability.</p>
+<p><strong>lush:</strong> Lush combines Lua&#x27;s simplicity with shell command integration nicely. The backtick syntax for command execution is intuitive, and the Lua-based file I/O and string processing felt natural. However, the file globbing required some manual parsing and filtering that felt a bit verbose compared to dedicated shell scripting. Overall, it strikes a good balance between scripting convenience and programming language features.</p>
+</div>
+        </div>
+
+        <div class="task-detail">
+            <h3>pipeline_transform <span class="cat">[a]</span>
+                <span class="pass">bash=PASS</span>
+                <span class="pass">lush=PASS</span>
+            </h3>
+            <table class="scores">
+                <thead><tr><th>Metric</th><th>Bash</th><th>Lush</th><th>Diff</th></tr></thead>
+                <tbody><tr><td>Readability</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Expressiveness</td><td>5</td><td>4</td><td class="neg">-1</td></tr><tr><td>Conciseness</td><td>5</td><td>3</td><td class="neg">-2</td></tr><tr><td>Error handling</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Overall preference</td><td>5</td><td>4</td><td class="neg">-1</td></tr><tr><td>Learning curve</td><td>3</td><td>4</td><td class="pos">+1</td></tr></tbody>
+            </table>
+            <div class="observations"><p><strong>bash:</strong> Bash excels at pipeline transformations like this - the pipe operator creates a natural flow that mirrors the logical steps. The regex in sed might be intimidating to newcomers, but the overall structure is intuitive. Error handling is implicit (pipes fail if any command fails) but lacks granular control.</p>
+<p><strong>lush:</strong> Lush felt very much like Lua, which made the text processing task straightforward. The pattern matching and string manipulation functions were intuitive. However, the manual deduplication logic required more verbose code than some other languages might need. Overall, it provided good control and clarity for this pipeline transformation task.</p>
+</div>
+        </div>
+
+        <div class="task-detail">
+            <h3>process_exit_codes <span class="cat">[a]</span>
+                <span class="pass">bash=PASS</span>
+                <span class="pass">lush=PASS</span>
+            </h3>
+            <table class="scores">
+                <thead><tr><th>Metric</th><th>Bash</th><th>Lush</th><th>Diff</th></tr></thead>
+                <tbody><tr><td>Readability</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Expressiveness</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Conciseness</td><td>5</td><td>5</td><td class="">0</td></tr><tr><td>Error handling</td><td>3</td><td>3</td><td class="">0</td></tr><tr><td>Overall preference</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Learning curve</td><td>3</td><td>4</td><td class="pos">+1</td></tr></tbody>
+            </table>
+            <div class="observations"><p><strong>bash:</strong> Bash is well-suited for this task since it naturally handles command execution and exit codes. The main challenges are bash-specific syntax quirks like the read loop condition and variable arithmetic. The use of eval introduces potential security concerns but is necessary for dynamic command execution. Overall, bash feels like the right tool for this system administration type task.</p>
+<p><strong>lush:</strong> Lush combines the simplicity of shell scripting with Lua&#x27;s readability. The command execution syntax `${command}` is intuitive and the ability to access exit codes via .code is clean. The Lua-based control structures and string handling make it much more readable than pure bash while maintaining the shell&#x27;s natural command execution feel.</p>
+</div>
+        </div>
+
+        <div class="task-detail">
+            <h3>reverse_string <span class="cat">[a]</span>
+                <span class="pass">bash=PASS</span>
+                <span class="pass">lush=PASS</span>
+            </h3>
+            <table class="scores">
+                <thead><tr><th>Metric</th><th>Bash</th><th>Lush</th><th>Diff</th></tr></thead>
+                <tbody><tr><td>Readability</td><td>5</td><td>5</td><td class="">0</td></tr><tr><td>Expressiveness</td><td>5</td><td>5</td><td class="">0</td></tr><tr><td>Conciseness</td><td>5</td><td>5</td><td class="">0</td></tr><tr><td>Error handling</td><td>3</td><td>3</td><td class="">0</td></tr><tr><td>Overall preference</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Learning curve</td><td>4</td><td>4</td><td class="">0</td></tr></tbody>
+            </table>
+            <div class="observations"><p><strong>bash:</strong> Bash excels at text manipulation tasks like this due to its built-in utilities like &#x27;rev&#x27;. The solution is extremely concise and leverages the shell&#x27;s natural pipeline approach. However, error handling would require additional checks for edge cases like empty input or command failures.</p>
+<p><strong>lush:</strong> Lush appears to be Lua-based with very familiar syntax and built-in string manipulation functions. The solution was extremely straightforward - just read input and use the built-in reverse function. The language feels mature and well-designed for simple scripting tasks like this.</p>
+</div>
+        </div>
+
+        <div class="task-detail">
+            <h3>two_sum <span class="cat">[a]</span>
+                <span class="pass">bash=PASS</span>
+                <span class="pass">lush=PASS</span>
+            </h3>
+            <table class="scores">
+                <thead><tr><th>Metric</th><th>Bash</th><th>Lush</th><th>Diff</th></tr></thead>
+                <tbody><tr><td>Readability</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Expressiveness</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Conciseness</td><td>4</td><td>3</td><td class="neg">-1</td></tr><tr><td>Error handling</td><td>2</td><td>2</td><td class="">0</td></tr><tr><td>Overall preference</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Learning curve</td><td>3</td><td>4</td><td class="pos">+1</td></tr></tbody>
+            </table>
+            <div class="observations"><p><strong>bash:</strong> Bash works for simple algorithmic problems but lacks data structures and type safety that would make this more robust. The C-style for loop syntax feels awkward compared to bash&#x27;s typical idioms, and array handling is somewhat clunky. Better suited for text processing and system tasks than algorithmic problems.</p>
+<p><strong>lush:</strong> Lua&#x27;s syntax is clean and straightforward for this algorithmic problem. The hash table implementation using tables works well, and string parsing with gmatch is reasonably elegant. However, the input parsing required some manual work, and there&#x27;s limited built-in error handling. The 1-based indexing required careful adjustment for 0-based output. Overall functional but not particularly specialized for competitive programming tasks.</p>
+</div>
+        </div>
+
+        <div class="task-detail">
+            <h3>csv_transform <span class="cat">[b]</span>
+                <span class="pass">bash=PASS</span>
+                <span class="pass">lush=PASS</span>
+            </h3>
+            <table class="scores">
+                <thead><tr><th>Metric</th><th>Bash</th><th>Lush</th><th>Diff</th></tr></thead>
+                <tbody><tr><td>Readability</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Expressiveness</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Conciseness</td><td>5</td><td>5</td><td class="">0</td></tr><tr><td>Error handling</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Overall preference</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Learning curve</td><td>3</td><td>4</td><td class="pos">+1</td></tr></tbody>
+            </table>
+            <div class="observations"><p><strong>bash:</strong> Bash excels at simple text processing tasks like this CSV transformation. The IFS mechanism and read command make parsing straightforward, and the solution is very concise. However, bash&#x27;s quirky syntax (like the `|| [[ -n &quot;$name&quot; ]]` construct for handling files without trailing newlines) can be confusing for newcomers. For more complex CSV handling with edge cases, a dedicated tool or language might be better.</p>
+<p><strong>lush:</strong> Lush&#x27;s Lua-based syntax made the CSV parsing task quite natural. The pattern matching with match() worked well for simple CSV parsing, and the io functions provided clean file handling. The solution was concise and readable, though proper CSV parsing (handling quoted fields, escapes) would require more complex regex or a dedicated library.</p>
+</div>
+        </div>
+
+        <div class="task-detail">
+            <h3>env_path_builder <span class="cat">[b]</span>
+                <span class="pass">bash=PASS</span>
+                <span class="pass">lush=PASS</span>
+            </h3>
+            <table class="scores">
+                <thead><tr><th>Metric</th><th>Bash</th><th>Lush</th><th>Diff</th></tr></thead>
+                <tbody><tr><td>Readability</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Expressiveness</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Conciseness</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Error handling</td><td>3</td><td>3</td><td class="">0</td></tr><tr><td>Overall preference</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Learning curve</td><td>3</td><td>3</td><td class="">0</td></tr></tbody>
+            </table>
+            <div class="observations"><p><strong>bash:</strong> Bash is well-suited for PATH manipulation tasks since it&#x27;s designed for system administration. The string manipulation features work naturally for this problem, though the syntax quirks (like the pattern matching in conditionals) might confuse newcomers. The solution handles edge cases like empty input and duplicate detection efficiently.</p>
+<p><strong>lush:</strong> Lush&#x27;s combination of Lua scripting with shell-like environment variable access ($MYPATH) made this task quite natural. The string manipulation and pattern matching capabilities were well-suited for path building. However, the mix of Lua and shell syntax might confuse developers not familiar with both paradigms.</p>
+</div>
+        </div>
+
+        <div class="task-detail">
+            <h3>log_parser <span class="cat">[b]</span>
+                <span class="pass">bash=PASS</span>
+                <span class="pass">lush=PASS</span>
+            </h3>
+            <table class="scores">
+                <thead><tr><th>Metric</th><th>Bash</th><th>Lush</th><th>Diff</th></tr></thead>
+                <tbody><tr><td>Readability</td><td>3</td><td>5</td><td class="pos">+2</td></tr><tr><td>Expressiveness</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Conciseness</td><td>5</td><td>4</td><td class="neg">-1</td></tr><tr><td>Error handling</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Overall preference</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Learning curve</td><td>2</td><td>4</td><td class="pos">+2</td></tr></tbody>
+            </table>
+            <div class="observations"><p><strong>bash:</strong> Bash excels at text processing pipelines like this, making it very concise. However, the syntax for robust input handling and parameter expansion can be cryptic. The pipeline approach is elegant but debugging can be challenging since errors may not propagate clearly through the chain.</p>
+<p><strong>lush:</strong> Lua&#x27;s syntax is clean and readable for text processing tasks. The pattern matching with string.match() worked well for parsing log lines. However, the manual table sorting approach feels slightly verbose compared to languages with built-in sorted collections. The &#x27;or 0&#x27; idiom for default values is elegant. Overall, Lua provides a good balance of simplicity and power for this type of scripting task.</p>
+</div>
+        </div>
+
+        <div class="task-detail">
+            <h3>pipeline_word_freq <span class="cat">[b]</span>
+                <span class="pass">bash=PASS</span>
+                <span class="pass">lush=PASS</span>
+            </h3>
+            <table class="scores">
+                <thead><tr><th>Metric</th><th>Bash</th><th>Lush</th><th>Diff</th></tr></thead>
+                <tbody><tr><td>Readability</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Expressiveness</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Conciseness</td><td>5</td><td>4</td><td class="neg">-1</td></tr><tr><td>Error handling</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Overall preference</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Learning curve</td><td>2</td><td>4</td><td class="pos">+2</td></tr></tbody>
+            </table>
+            <div class="observations"><p><strong>bash:</strong> Bash excels at text processing pipelines with its built-in tools like tr, grep, sort, and uniq. The solution is extremely concise but requires knowledge of Unix command-line tools and their options. The pipe-based approach is natural for this problem, but the syntax can be cryptic with options like &#x27;tr -cs&#x27; and &#x27;sort -k1,1rn&#x27;. The final while loop with the complex condition is necessary but makes the code less readable.</p>
+<p><strong>lush:</strong> Lush feels very much like Lua with clean syntax for text processing. The gmatch function for pattern matching and the flexible table structure made the word frequency counting natural. The sorting with custom comparison functions worked smoothly. Overall, it struck a good balance between simplicity and power for this text processing task.</p>
+</div>
+        </div>
+
+</body>
+</html>

tasks/category_a/env_config.toml

@@ -0,0 +1,32 @@
+name = "env_config"
+category = "a"
+description = """
+Read a config format from stdin where each line is "KEY=VALUE".
+For each line, set an environment variable with that key and value.
+After processing all lines, run the command `env` and print only the variables
+that were set from the input, sorted alphabetically by key, in "KEY=VALUE" format.
+
+You must actually set these as environment variables and retrieve them back
+(not just echo the input).
+"""
+
+[[test_cases]]
+stdin = """APP_NAME=myapp
+APP_PORT=8080
+APP_DEBUG=true"""
+expected_stdout = """APP_DEBUG=true
+APP_NAME=myapp
+APP_PORT=8080"""
+env = {}
+
+[[test_cases]]
+stdin = """DB_HOST=localhost
+DB_PORT=5432"""
+expected_stdout = """DB_HOST=localhost
+DB_PORT=5432"""
+env = {}
+
+[[test_cases]]
+stdin = "SINGLE_VAR=hello"
+expected_stdout = "SINGLE_VAR=hello"
+env = {}

tasks/category_a/file_organizer.toml

@@ -0,0 +1,28 @@
+name = "file_organizer"
+category = "a"
+description = """
+You are given a working directory containing several files with extensions.
+Read a list of extension-to-directory mappings from stdin, one per line, in the format:
+  ext:dirname
+
+For example, "txt:documents" means move all .txt files into a subdirectory called "documents".
+
+Create the target directories if they don't exist, then move matching files into them.
+After processing, print each moved file as "filename -> dirname/filename", sorted alphabetically by filename.
+Files that don't match any mapping should be left in place (don't print anything for them).
+"""
+
+[[test_cases]]
+stdin = """txt:documents
+log:logs"""
+expected_stdout = """app.log -> logs/app.log
+notes.txt -> documents/notes.txt
+readme.txt -> documents/readme.txt"""
+setup_files = { "notes.txt" = "some notes", "readme.txt" = "a readme", "app.log" = "log data", "image.png" = "fake png" }
+expected_files = { "documents/notes.txt" = "some notes", "documents/readme.txt" = "a readme", "logs/app.log" = "log data", "image.png" = "fake png" }
+
+[[test_cases]]
+stdin = "csv:data"
+expected_stdout = """report.csv -> data/report.csv"""
+setup_files = { "report.csv" = "a,b,c", "other.txt" = "hello" }
+expected_files = { "data/report.csv" = "a,b,c", "other.txt" = "hello" }

tasks/category_a/fizzbuzz.toml

@@ -0,0 +1,38 @@
+name = "fizzbuzz"
+category = "a"
+description = """
+Read a single integer N from stdin. Print numbers from 1 to N, one per line.
+For multiples of 3, print "Fizz" instead of the number.
+For multiples of 5, print "Buzz" instead of the number.
+For multiples of both 3 and 5, print "FizzBuzz" instead of the number.
+"""
+
+[[test_cases]]
+stdin = "15"
+expected_stdout = """1
+2
+Fizz
+4
+Buzz
+Fizz
+7
+8
+Fizz
+Buzz
+11
+Fizz
+13
+14
+FizzBuzz"""
+
+[[test_cases]]
+stdin = "5"
+expected_stdout = """1
+2
+Fizz
+4
+Buzz"""
+
+[[test_cases]]
+stdin = "1"
+expected_stdout = "1"

tasks/category_a/multi_file_search.toml

@@ -0,0 +1,29 @@
+name = "multi_file_search"
+category = "a"
+description = """
+You are given a working directory containing several text files.
+Read a search pattern (a simple string, not regex) from stdin.
+Search all .txt files in the working directory for lines containing that pattern (case-sensitive).
+
+Print matching results in the format: "filename:line_number:line_content"
+Results should be sorted first by filename, then by line number.
+Line numbers are 1-based.
+"""
+
+[[test_cases]]
+stdin = "error"
+expected_stdout = """app.txt:2:found an error here
+app.txt:4:another error occurred
+system.txt:1:error on startup"""
+setup_files = { "app.txt" = "all good\nfound an error here\nno problem\nanother error occurred", "system.txt" = "error on startup\nrunning fine\nshutdown", "data.csv" = "error,value\n1,2" }
+
+[[test_cases]]
+stdin = "hello"
+expected_stdout = """a.txt:1:hello world
+b.txt:2:say hello"""
+setup_files = { "a.txt" = "hello world\ngoodbye", "b.txt" = "greetings\nsay hello" }
+
+[[test_cases]]
+stdin = "notfound"
+expected_stdout = ""
+setup_files = { "test.txt" = "nothing matches here" }

tasks/category_a/pipeline_transform.toml

@@ -0,0 +1,37 @@
+name = "pipeline_transform"
+category = "a"
+description = """
+Read lines from stdin. Build a pipeline that:
+1. Filters to only lines containing the word "error" (case-insensitive)
+2. Extracts the portion after the first colon (trimming leading whitespace)
+3. Sorts the results alphabetically
+4. Removes duplicate lines
+
+Print the final result to stdout, one line per line.
+"""
+
+[[test_cases]]
+stdin = """INFO: server started
+ERROR: disk full
+WARN: low memory
+error: connection refused
+ERROR: disk full
+INFO: request handled
+Error: timeout reached"""
+expected_stdout = """connection refused
+disk full
+timeout reached"""
+
+[[test_cases]]
+stdin = """ERROR: alpha
+ERROR: charlie
+ERROR: bravo
+ERROR: alpha"""
+expected_stdout = """alpha
+bravo
+charlie"""
+
+[[test_cases]]
+stdin = """INFO: all good
+WARN: nothing here"""
+expected_stdout = ""

tasks/category_a/process_exit_codes.toml

@@ -0,0 +1,39 @@
+name = "process_exit_codes"
+category = "a"
+description = """
+Read commands from stdin, one per line. Execute each command as a subprocess.
+For each command, print: "command: exit_code" where command is the original command text
+and exit_code is the numeric exit code of the process.
+
+After all commands, print a blank line followed by a summary line:
+"passed: N, failed: M"
+where N is the count of commands with exit code 0, and M is the count with non-zero exit codes.
+"""
+
+[[test_cases]]
+stdin = """true
+false
+echo hello
+test -f /nonexistent"""
+expected_stdout = """true: 0
+false: 1
+echo hello: 0
+test -f /nonexistent: 1
+
+passed: 2, failed: 2"""
+
+[[test_cases]]
+stdin = """true
+true
+true"""
+expected_stdout = """true: 0
+true: 0
+true: 0
+
+passed: 3, failed: 0"""
+
+[[test_cases]]
+stdin = "false"
+expected_stdout = """false: 1
+
+passed: 0, failed: 1"""

tasks/category_a/reverse_string.toml

@@ -0,0 +1,21 @@
+name = "reverse_string"
+category = "a"
+description = """
+Read a single line from stdin and print it reversed to stdout.
+"""
+
+[[test_cases]]
+stdin = "hello"
+expected_stdout = "olleh"
+
+[[test_cases]]
+stdin = "abcdef"
+expected_stdout = "fedcba"
+
+[[test_cases]]
+stdin = "racecar"
+expected_stdout = "racecar"
+
+[[test_cases]]
+stdin = "a"
+expected_stdout = "a"

tasks/category_a/two_sum.toml

@@ -0,0 +1,24 @@
+name = "two_sum"
+category = "a"
+description = """
+Read input from stdin. The first line contains a target integer.
+The second line contains space-separated integers (the array).
+Find two indices (0-based) such that the numbers at those indices add up to the target.
+Print the two indices on a single line, space-separated, smaller index first.
+There is exactly one solution.
+"""
+
+[[test_cases]]
+stdin = """9
+2 7 11 15"""
+expected_stdout = "0 1"
+
+[[test_cases]]
+stdin = """6
+3 2 4"""
+expected_stdout = "1 2"
+
+[[test_cases]]
+stdin = """6
+3 3"""
+expected_stdout = "0 1"

tasks/category_b/csv_transform.toml

@@ -0,0 +1,28 @@
+name = "csv_transform"
+category = "b"
+description = """
+Read CSV data from stdin. The first line is a header.
+Each subsequent line has fields: name,age,city
+Print each record as "name is age years old and lives in city", one per line.
+Skip the header in the output.
+"""
+
+bash_source = """
+#!/bin/bash
+read -r header  # skip header
+while IFS=',' read -r name age city || [[ -n "$name" ]]; do
+    echo "$name is $age years old and lives in $city"
+done
+"""
+
+[[test_cases]]
+stdin = """name,age,city
+Alice,30,Paris
+Bob,25,London"""
+expected_stdout = """Alice is 30 years old and lives in Paris
+Bob is 25 years old and lives in London"""
+
+[[test_cases]]
+stdin = """name,age,city
+Charlie,40,Tokyo"""
+expected_stdout = "Charlie is 40 years old and lives in Tokyo"

tasks/category_b/env_path_builder.toml

@@ -0,0 +1,39 @@
+name = "env_path_builder"
+category = "b"
+description = """
+Read directory paths from stdin, one per line.
+Append each to the MYPATH environment variable (colon-separated), skipping duplicates.
+The initial value of MYPATH is provided via the environment (may be empty).
+Print the final value of MYPATH to stdout.
+"""
+
+bash_source = """
+#!/bin/bash
+while IFS= read -r dir || [[ -n "$dir" ]]; do
+    if [[ -z "$MYPATH" ]]; then
+        export MYPATH="$dir"
+    elif [[ ":$MYPATH:" != *":$dir:"* ]]; then
+        export MYPATH="$MYPATH:$dir"
+    fi
+done
+echo "$MYPATH"
+"""
+
+[[test_cases]]
+stdin = """/usr/local/bin
+/usr/bin
+/usr/local/bin
+/opt/bin"""
+expected_stdout = "/usr/local/bin:/usr/bin:/opt/bin"
+env = { "MYPATH" = "" }
+
+[[test_cases]]
+stdin = """/new/path
+/existing"""
+expected_stdout = "/already/here:/new/path:/existing"
+env = { "MYPATH" = "/already/here" }
+
+[[test_cases]]
+stdin = "/only"
+expected_stdout = "/only"
+env = { "MYPATH" = "" }

tasks/category_b/log_parser.toml

@@ -0,0 +1,33 @@
+name = "log_parser"
+category = "b"
+description = """
+Read log lines from stdin. Each line has the format: "LEVEL: message"
+where LEVEL is one of ERROR, WARN, INFO.
+Count occurrences of each level and print a summary sorted by level name.
+Format: "LEVEL: count"
+"""
+
+bash_source = """
+#!/bin/bash
+while IFS= read -r line || [[ -n "$line" ]]; do
+    echo "${line%%:*}"
+done | sort | uniq -c | while read -r count level; do
+    echo "$level: $count"
+done
+"""
+
+[[test_cases]]
+stdin = """ERROR: disk full
+INFO: started
+WARN: low memory
+ERROR: timeout
+INFO: completed"""
+expected_stdout = """ERROR: 2
+INFO: 2
+WARN: 1"""
+
+[[test_cases]]
+stdin = """INFO: boot
+INFO: ready
+INFO: shutdown"""
+expected_stdout = "INFO: 3"

tasks/category_b/pipeline_word_freq.toml

@@ -0,0 +1,36 @@
+name = "pipeline_word_freq"
+category = "b"
+description = """
+Read text from stdin. Count the frequency of each word (case-insensitive, only alphabetic characters count as words).
+Print the top 5 most frequent words in descending order of frequency, in the format:
+"count word"
+If two words have the same count, sort them alphabetically.
+If there are fewer than 5 unique words, print all of them.
+"""
+
+bash_source = """
+#!/bin/bash
+tr '[:upper:]' '[:lower:]' | tr -cs '[:alpha:]' '\n' | grep -v '^$' | sort | uniq -c | sort -k1,1rn -k2,2 | head -5 | while read -r count word || [[ -n "$word" ]]; do
+    echo "$count $word"
+done
+"""
+
+[[test_cases]]
+stdin = """The quick brown fox jumps over the lazy dog.
+The dog barked at the fox. The fox ran away."""
+expected_stdout = """5 the
+3 fox
+2 dog
+1 at
+1 away"""
+
+[[test_cases]]
+stdin = "hello hello world"
+expected_stdout = """2 hello
+1 world"""
+
+[[test_cases]]
+stdin = "One one ONE two TWO two Three three three three"
+expected_stdout = """4 three
+3 one
+3 two"""

uv.lock

@@ -0,0 +1,874 @@
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