be8d657b24
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
33 lines
820 B
TOML
33 lines
820 B
TOML
name = "env_config"
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category = "a"
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description = """
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Read a config format from stdin where each line is "KEY=VALUE".
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For each line, set an environment variable with that key and value.
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After processing all lines, run the command `env` and print only the variables
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that were set from the input, sorted alphabetically by key, in "KEY=VALUE" format.
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You must actually set these as environment variables and retrieve them back
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(not just echo the input).
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"""
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[[test_cases]]
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stdin = """APP_NAME=myapp
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APP_PORT=8080
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APP_DEBUG=true"""
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expected_stdout = """APP_DEBUG=true
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APP_NAME=myapp
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APP_PORT=8080"""
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env = {}
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[[test_cases]]
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stdin = """DB_HOST=localhost
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DB_PORT=5432"""
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expected_stdout = """DB_HOST=localhost
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DB_PORT=5432"""
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env = {}
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[[test_cases]]
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stdin = "SINGLE_VAR=hello"
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expected_stdout = "SINGLE_VAR=hello"
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env = {}
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