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io.github.phoenice-labs/universal-test-framework

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run_mutation_tests

Run mutation testing on a source and test file pair. Returns coverage metrics with auto-detected adapters for Python, JavaScript, TypeScript, Java, and Go.

Instructions

Run mutation testing on a source+test file pair and return coverage metrics.

Supports mutmut (Python), Stryker (JS/TS), PIT (Java), and gremlins (Go). The adapter is auto-detected based on language and tool availability.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageYesLanguage of the files (python | javascript | typescript | java | go)
test_fileYesPath to the test file to run against mutants
block_belowNoScore below which the result is flagged as blocked (default: 0.50)
project_dirNoProject root directory (defaults to cwd)
source_fileYesPath to the source file to mutate
minimum_scoreNoThreshold to pass (default: 0.70 = 70% killed)
timeout_secondsNoMutation run timeout in seconds (default: 300)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It mentions auto-detection of adapters and return of coverage metrics, but lacks details on side effects, permissions, or failure behavior. The timeout parameter is in the schema, not the description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences that front-load the purpose followed by supported tools. No wasted words, clear and efficient structure.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the 7 parameters (3 required) and existence of an output schema, the description covers the main purpose and tool support. It could elaborate on parameter roles like block_below and minimum_score, but the output schema compensates for return values.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description does not add meaning beyond the schema; it only mentions supported tools and auto-detection, not parameter details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'run' and the resource 'mutation testing on a source+test file pair'. It distinguishes from sibling tools like 'run_tests' and 'analyze_coverage' by focusing specifically on mutation testing and listing supported adapters.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for mutation testing but does not explicitly state when to use this tool versus alternatives. No when-not or alternative tool names are provided beyond the sibling list.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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