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rerun_mutmut_on_survivor

Rerun mutation tests on surviving mutations after test updates to verify fixes and improve test coverage in Python projects using mutmut CLI.

Instructions

Rerun mutmut on specific surviving mutations or all survivors after test updates using the mutmut CLI. Returns the plain text output.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mutation_idNo
venv_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function 'rerun_mutmut_on_survivor' executes the mutmut CLI command with either --rerun or --rerun-all based on the provided mutation_id.
    def rerun_mutmut_on_survivor(mutation_id: Optional[str] = None, venv_path: Optional[str] = None) -> str:
        """
        Rerun mutmut on specific surviving mutations or all survivors after test updates using the mutmut CLI.
        Returns the plain text output.
        """
        if mutation_id:
            return _run_mutmut_cli(["run", "--rerun", mutation_id], venv_path)
        else:
            return _run_mutmut_cli(["run", "--rerun-all"], venv_path)
  • mutmut_mcp.py:185-185 (registration)
    Registration of 'rerun_mutmut_on_survivor' as an MCP tool using mcp.tool().
    mcp.tool()(rerun_mutmut_on_survivor)
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions using 'mutmut CLI' and returning 'plain text output', but lacks critical behavioral details: whether this is read-only or modifies data, permission requirements, side effects (e.g., cache updates), or error handling. This is inadequate for a tool with potential mutation implications.

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

Conciseness4/5

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

Two concise sentences front-load the core purpose and output. No wasted words, though it could be slightly more structured by explicitly listing parameters.

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

Completeness3/5

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

With an output schema present, return values needn't be detailed. However, for a tool with 2 parameters (0% schema coverage) and no annotations, the description is too sparse—it doesn't clarify parameter roles, prerequisites, or behavioral risks, making it incomplete for safe agent use.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It only vaguely references 'specific surviving mutations or all survivors', hinting at 'mutation_id' usage but not explaining its format or purpose. No mention of 'venv_path' at all. This leaves both parameters largely undocumented.

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

Purpose4/5

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

The description clearly states the action ('Rerun mutmut') and target ('on specific surviving mutations or all survivors after test updates'), distinguishing it from siblings like 'run_mutmut' (initial run) and 'show_survivors' (view only). However, it doesn't explicitly contrast with 'prioritize_survivors' (which likely organizes rather than executes).

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?

Usage is implied by context: use after test updates to re-evaluate survivors, with 'mutation_id' for specific ones or null for all. No explicit when-not-to-use guidance or alternatives are mentioned, though it's logically distinct from 'run_mutmut' for initial runs.

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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