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Cormac Shannon 18ce7e57cf Revamp questionnaire, parallelize run-all, add new tasks 
- Replace 6 compound Likert questions with 12 atomic ones grouped by
  dimension (syntax, expressiveness, data/IO, errors, overall); drop
  free-form question. Responses now stored as ints, not strings.
- Back-compat layer maps legacy keys to new dimensions so existing
  results still render.
- Parallelize run-all with ThreadPoolExecutor (configurable workers)
  and add a thread-safe min-request-interval rate limiter to the
  Anthropic provider.
- Add new tasks: path_normalizer, todo_manager, currency_converter,
  locale_weather_url, network_info_parser, url_normalizer.
2026-04-07 19:07:21 +01:00

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<!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; }
</style>
</head>
<body>
<h1>Lush vs Bash Benchmark Report</h1>
<p class="meta">Model: claude-sonnet-4-20250514 &middot; Latest run: 20260401T183152Z &middot; Tasks: 18</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>fizzbuzz</td><td>algorithm</td>
<td class="pass">PASS</td><td>1</td>
<td class="pass">PASS</td><td>1</td>
</tr><tr>
<td>reverse_string</td><td>algorithm</td>
<td class="pass">PASS</td><td>1</td>
<td class="pass">PASS</td><td>1</td>
</tr><tr>
<td>two_sum</td><td>algorithm</td>
<td class="pass">PASS</td><td>1</td>
<td class="pass">PASS</td><td>1</td>
</tr><tr>
<td>env_config</td><td>environment</td>
<td class="fail">FAIL</td><td>4</td>
<td class="pass">PASS</td><td>2</td>
</tr><tr>
<td>env_path_builder</td><td>environment</td>
<td class="pass">PASS</td><td>0</td>
<td class="pass">PASS</td><td>1</td>
</tr><tr>
<td>path_normalizer</td><td>environment</td>
<td class="pass">PASS</td><td>0</td>
<td class="pass">PASS</td><td>1</td>
</tr><tr>
<td>file_organizer</td><td>filesystem</td>
<td class="fail">FAIL</td><td>4</td>
<td class="pass">PASS</td><td>1</td>
</tr><tr>
<td>multi_file_search</td><td>filesystem</td>
<td class="pass">PASS</td><td>1</td>
<td class="pass">PASS</td><td>2</td>
</tr><tr>
<td>todo_manager</td><td>filesystem</td>
<td class="pass">PASS</td><td>0</td>
<td class="pass">PASS</td><td>1</td>
</tr><tr>
<td>csv_transform</td><td>pipeline</td>
<td class="pass">PASS</td><td>0</td>
<td class="pass">PASS</td><td>1</td>
</tr><tr>
<td>currency_converter</td><td>pipeline</td>
<td class="pass">PASS</td><td>0</td>
<td class="pass">PASS</td><td>1</td>
</tr><tr>
<td>locale_weather_url</td><td>pipeline</td>
<td class="pass">PASS</td><td>0</td>
<td class="pass">PASS</td><td>1</td>
</tr><tr>
<td>log_parser</td><td>pipeline</td>
<td class="pass">PASS</td><td>0</td>
<td class="pass">PASS</td><td>1</td>
</tr><tr>
<td>network_info_parser</td><td>pipeline</td>
<td class="pass">PASS</td><td>0</td>
<td class="pass">PASS</td><td>1</td>
</tr><tr>
<td>pipeline_transform</td><td>pipeline</td>
<td class="pass">PASS</td><td>1</td>
<td class="pass">PASS</td><td>1</td>
</tr><tr>
<td>pipeline_word_freq</td><td>pipeline</td>
<td class="pass">PASS</td><td>0</td>
<td class="pass">PASS</td><td>1</td>
</tr><tr>
<td>url_normalizer</td><td>pipeline</td>
<td class="pass">PASS</td><td>0</td>
<td class="pass">PASS</td><td>1</td>
</tr><tr>
<td>process_exit_codes</td><td>process</td>
<td class="pass">PASS</td><td>4</td>
<td class="pass">PASS</td><td>1</td>
</tr></tbody>
<tfoot><tr>
<td><strong>Total</strong></td><td></td>
<td><strong>16/18</strong></td><td></td>
<td><strong>18/18</strong></td><td></td>
</tr></tfoot>
</table>
<h2>Per-Category Summary</h2>
<table>
<thead><tr>
<th>Category</th>
<th>Bash Pass</th><th>Lush Pass</th>
<th>Bash Avg Turns</th><th>Lush Avg Turns</th>
<th>Bash Avg Score</th><th>Lush Avg Score</th>
</tr></thead>
<tbody><tr>
<td>algorithm</td>
<td>3/3</td><td>3/3</td>
<td>1.0</td><td>1.0</td>
<td>3.5</td><td>3.9</td>
</tr><tr>
<td>environment</td>
<td>2/3</td><td>3/3</td>
<td>4.0</td><td>1.3</td>
<td>2.8</td><td>3.9</td>
</tr><tr>
<td>filesystem</td>
<td>2/3</td><td>3/3</td>
<td>2.5</td><td>1.3</td>
<td>3.1</td><td>3.8</td>
</tr><tr>
<td>pipeline</td>
<td>8/8</td><td>8/8</td>
<td>1.0</td><td>1.0</td>
<td>3.0</td><td>3.9</td>
</tr><tr>
<td>process</td>
<td>1/1</td><td>1/1</td>
<td>4.0</td><td>1.0</td>
<td>3.2</td><td>4.0</td>
</tr></tbody>
</table>
<h2>Questionnaire Scores</h2>
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alt="Questionnaire comparison"></div>
<h2>Questionnaire Scores by Category</h2>
<div class="chart"><img src="data:image/png;base64,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" alt="Per-category questionnaire"></div>
<h2>Agent Turns (Solve Mode)</h2>
<div class="chart"><img 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" alt="Turns comparison"></div>
<h2>Score Difference Heatmap (Lush - Bash)</h2>
<div class="chart"><img 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" alt="Score heatmap"></div>
<h2>Per-Category Breakdown</h2>
<h3>algorithm</h3><div class="chart"><img 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" alt="algorithm breakdown"></div><h3>environment</h3><div class="chart"><img 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alt="environment breakdown"></div><h3>filesystem</h3><div class="chart"><img 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" alt="filesystem breakdown"></div><h3>pipeline</h3><div class="chart"><img 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" alt="pipeline breakdown"></div><h3>process</h3><div class="chart"><img src="data:image/png;base64,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" alt="process breakdown"></div>
<h2>Per-Task Detail</h2>
<div class="task-detail">
<h3>fizzbuzz <span class="cat">[algorithm/solve]</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>Syntax clarity</td><td>3</td><td>5</td><td class="pos">+2</td></tr><tr><td>Signal-to-noise</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Familiar conventions</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Built-in operations</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>String operations</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Composition</td><td>5</td><td>3</td><td class="neg">-2</td></tr><tr><td>I/O ergonomics</td><td>5</td><td>4</td><td class="neg">-1</td></tr><tr><td>Data structures</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Error model</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Edge case support</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Learnability</td><td>3</td><td>5</td><td class="pos">+2</td></tr><tr><td>Fitness for task</td><td>4</td><td>4</td><td class="">0</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>reverse_string <span class="cat">[algorithm/solve]</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>Syntax clarity</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Signal-to-noise</td><td>5</td><td>4</td><td class="neg">-1</td></tr><tr><td>Familiar conventions</td><td>2</td><td>5</td><td class="pos">+3</td></tr><tr><td>Built-in operations</td><td>5</td><td>5</td><td class="">0</td></tr><tr><td>String operations</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Composition</td><td>5</td><td>4</td><td class="neg">-1</td></tr><tr><td>I/O ergonomics</td><td>5</td><td>4</td><td class="neg">-1</td></tr><tr><td>Data structures</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Error model</td><td>3</td><td>3</td><td class="">0</td></tr><tr><td>Edge case support</td><td>3</td><td>3</td><td class="">0</td></tr><tr><td>Learnability</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Fitness for task</td><td>4</td><td>4</td><td class="">0</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>two_sum <span class="cat">[algorithm/solve]</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>Syntax clarity</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Signal-to-noise</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Familiar conventions</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Built-in operations</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>String operations</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Composition</td><td>4</td><td>3</td><td class="neg">-1</td></tr><tr><td>I/O ergonomics</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Data structures</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Error model</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Edge case support</td><td>2</td><td>2</td><td class="">0</td></tr><tr><td>Learnability</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Fitness for task</td><td>2</td><td>4</td><td class="pos">+2</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>env_config <span class="cat">[environment/solve]</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>Syntax clarity</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Signal-to-noise</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Familiar conventions</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Built-in operations</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>String operations</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Composition</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>I/O ergonomics</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Data structures</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Error model</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Edge case support</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Learnability</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Fitness for task</td><td>3</td><td>5</td><td class="pos">+2</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>env_path_builder <span class="cat">[environment/convert]</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>Syntax clarity</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Signal-to-noise</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Familiar conventions</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Built-in operations</td><td>3</td><td>3</td><td class="">0</td></tr><tr><td>String operations</td><td>3</td><td>3</td><td class="">0</td></tr><tr><td>Composition</td><td>4</td><td>3</td><td class="neg">-1</td></tr><tr><td>I/O ergonomics</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Data structures</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Error model</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Edge case support</td><td>3</td><td>3</td><td class="">0</td></tr><tr><td>Learnability</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Fitness for task</td><td>4</td><td>4</td><td class="">0</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>path_normalizer <span class="cat">[environment/convert]</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>Syntax clarity</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Signal-to-noise</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Familiar conventions</td><td>2</td><td>5</td><td class="pos">+3</td></tr><tr><td>Built-in operations</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>String operations</td><td>3</td><td>5</td><td class="pos">+2</td></tr><tr><td>Composition</td><td>4</td><td>3</td><td class="neg">-1</td></tr><tr><td>I/O ergonomics</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Data structures</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Error model</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Edge case support</td><td>3</td><td>3</td><td class="">0</td></tr><tr><td>Learnability</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Fitness for task</td><td>3</td><td>4</td><td class="pos">+1</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>file_organizer <span class="cat">[filesystem/solve]</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>Syntax clarity</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Signal-to-noise</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Familiar conventions</td><td>2</td><td>5</td><td class="pos">+3</td></tr><tr><td>Built-in operations</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>String operations</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Composition</td><td>4</td><td>3</td><td class="neg">-1</td></tr><tr><td>I/O ergonomics</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Data structures</td><td>3</td><td>5</td><td class="pos">+2</td></tr><tr><td>Error model</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Edge case support</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Learnability</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Fitness for task</td><td>4</td><td>5</td><td class="pos">+1</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>multi_file_search <span class="cat">[filesystem/solve]</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>Syntax clarity</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Signal-to-noise</td><td>4</td><td>3</td><td class="neg">-1</td></tr><tr><td>Familiar conventions</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Built-in operations</td><td>5</td><td>2</td><td class="neg">-3</td></tr><tr><td>String operations</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Composition</td><td>5</td><td>3</td><td class="neg">-2</td></tr><tr><td>I/O ergonomics</td><td>5</td><td>4</td><td class="neg">-1</td></tr><tr><td>Data structures</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Error model</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Edge case support</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Learnability</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Fitness for task</td><td>5</td><td>3</td><td class="neg">-2</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>todo_manager <span class="cat">[filesystem/convert]</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>Syntax clarity</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Signal-to-noise</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Familiar conventions</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Built-in operations</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>String operations</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Composition</td><td>4</td><td>3</td><td class="neg">-1</td></tr><tr><td>I/O ergonomics</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Data structures</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Error model</td><td>2</td><td>2</td><td class="">0</td></tr><tr><td>Edge case support</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Learnability</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Fitness for task</td><td>3</td><td>4</td><td class="pos">+1</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>csv_transform <span class="cat">[pipeline/convert]</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>Syntax clarity</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Signal-to-noise</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Familiar conventions</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Built-in operations</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>String operations</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Composition</td><td>5</td><td>3</td><td class="neg">-2</td></tr><tr><td>I/O ergonomics</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Data structures</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Error model</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Edge case support</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Learnability</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Fitness for task</td><td>4</td><td>4</td><td class="">0</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>currency_converter <span class="cat">[pipeline/convert]</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>Syntax clarity</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Signal-to-noise</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Familiar conventions</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Built-in operations</td><td>1</td><td>2</td><td class="pos">+1</td></tr><tr><td>String operations</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Composition</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>I/O ergonomics</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Data structures</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Error model</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Edge case support</td><td>3</td><td>3</td><td class="">0</td></tr><tr><td>Learnability</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Fitness for task</td><td>2</td><td>4</td><td class="pos">+2</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>locale_weather_url <span class="cat">[pipeline/convert]</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>Syntax clarity</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Signal-to-noise</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Familiar conventions</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Built-in operations</td><td>2</td><td>5</td><td class="pos">+3</td></tr><tr><td>String operations</td><td>3</td><td>5</td><td class="pos">+2</td></tr><tr><td>Composition</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>I/O ergonomics</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Data structures</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Error model</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Edge case support</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Learnability</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Fitness for task</td><td>4</td><td>5</td><td class="pos">+1</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>log_parser <span class="cat">[pipeline/convert]</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>Syntax clarity</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Signal-to-noise</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Familiar conventions</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Built-in operations</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>String operations</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Composition</td><td>5</td><td>3</td><td class="neg">-2</td></tr><tr><td>I/O ergonomics</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Data structures</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Error model</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Edge case support</td><td>3</td><td>3</td><td class="">0</td></tr><tr><td>Learnability</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Fitness for task</td><td>4</td><td>4</td><td class="">0</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>network_info_parser <span class="cat">[pipeline/convert]</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>Syntax clarity</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Signal-to-noise</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Familiar conventions</td><td>3</td><td>5</td><td class="pos">+2</td></tr><tr><td>Built-in operations</td><td>2</td><td>5</td><td class="pos">+3</td></tr><tr><td>String operations</td><td>2</td><td>5</td><td class="pos">+3</td></tr><tr><td>Composition</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>I/O ergonomics</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Data structures</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Error model</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Edge case support</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Learnability</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Fitness for task</td><td>4</td><td>5</td><td class="pos">+1</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>pipeline_transform <span class="cat">[pipeline/solve]</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>Syntax clarity</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Signal-to-noise</td><td>5</td><td>3</td><td class="neg">-2</td></tr><tr><td>Familiar conventions</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Built-in operations</td><td>5</td><td>3</td><td class="neg">-2</td></tr><tr><td>String operations</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Composition</td><td>5</td><td>2</td><td class="neg">-3</td></tr><tr><td>I/O ergonomics</td><td>5</td><td>4</td><td class="neg">-1</td></tr><tr><td>Data structures</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Error model</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Edge case support</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Learnability</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Fitness for task</td><td>5</td><td>3</td><td class="neg">-2</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>pipeline_word_freq <span class="cat">[pipeline/convert]</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>Syntax clarity</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Signal-to-noise</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Familiar conventions</td><td>2</td><td>5</td><td class="pos">+3</td></tr><tr><td>Built-in operations</td><td>5</td><td>4</td><td class="neg">-1</td></tr><tr><td>String operations</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Composition</td><td>5</td><td>3</td><td class="neg">-2</td></tr><tr><td>I/O ergonomics</td><td>5</td><td>4</td><td class="neg">-1</td></tr><tr><td>Data structures</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Error model</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Edge case support</td><td>3</td><td>3</td><td class="">0</td></tr><tr><td>Learnability</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Fitness for task</td><td>5</td><td>4</td><td class="neg">-1</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>url_normalizer <span class="cat">[pipeline/convert]</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>Syntax clarity</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Signal-to-noise</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Familiar conventions</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Built-in operations</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>String operations</td><td>3</td><td>5</td><td class="pos">+2</td></tr><tr><td>Composition</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>I/O ergonomics</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Data structures</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Error model</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Edge case support</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Learnability</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Fitness for task</td><td>3</td><td>4</td><td class="pos">+1</td></tr></tbody>
</table>
</div>
<div class="task-detail">
<h3>process_exit_codes <span class="cat">[process/solve]</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>Syntax clarity</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Signal-to-noise</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Familiar conventions</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Built-in operations</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>String operations</td><td>4</td><td>4</td><td class="">0</td></tr><tr><td>Composition</td><td>5</td><td>3</td><td class="neg">-2</td></tr><tr><td>I/O ergonomics</td><td>4</td><td>5</td><td class="pos">+1</td></tr><tr><td>Data structures</td><td>3</td><td>4</td><td class="pos">+1</td></tr><tr><td>Error model</td><td>3</td><td>3</td><td class="">0</td></tr><tr><td>Edge case support</td><td>2</td><td>3</td><td class="pos">+1</td></tr><tr><td>Learnability</td><td>2</td><td>4</td><td class="pos">+2</td></tr><tr><td>Fitness for task</td><td>5</td><td>5</td><td class="">0</td></tr></tbody>
</table>
</div>
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