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run_repository_fix

Run the repository pipeline and apply its result in one call, returning the canonical envelope for both stages. Use when you need to execute a fix and apply it immediately without separate review.

Instructions

Run the repository pipeline and then apply its result in one call, returning the canonical repository envelope for both stages. pipeline takes run_repository_pipeline's arguments and must complete through simulate (the call fails otherwise); apply takes apply_repository's arguments with mode defaulting to patch_only — the write modes still require the simulation gate to pass and write_permission=true. Use the separate stage tools when you need to review the plan or simulation before anything is written.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
applyNoapply_repository arguments (branch, message, PR fields, write_permission); mode defaults to patch_only.
pipelineNorun_repository_pipeline arguments; defaults to {}.
repository_idYesSaved repository connector id from list_connectors.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv0.1.3
    • addedInput schema / properties / apply / description
      Added value: +"apply_repository arguments (branch, message, PR fields, write_permission); mode defaults to patch_only."
    • addedInput schema / properties / pipeline / description
      Added value: +"run_repository_pipeline arguments; defaults to {}."
    • addedInput schema / properties / repository_id / description
      Added value: +"Saved repository connector id from list_connectors."
  2. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

Discloses that the pipeline must complete through simulate or the call fails, and that write modes require the simulation gate to pass and write_permission=true. This goes beyond the annotations (readOnlyHint=false, destructiveHint=false) and explains the operational constraints and failure conditions.

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, front-loaded with the core action, then the necessary caveats and usage guidance. No redundant phrasing or irrelevant detail.

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?

For a combined mutation tool with nested objects and no output schema, the description covers the main stages, prerequisites, failure conditions, and alternatives. It doesn't detail every possible apply mode or the exact envelope format, but these are likely defined elsewhere and the description provides sufficient context for correct usage.

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

Parameters4/5

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

Schema coverage is 100%, so the parameters are already documented. The description adds value by explaining that pipeline takes run_repository_pipeline's arguments and apply takes apply_repository's arguments with mode defaulting to patch_only, clarifying the nested object semantics and the write_permission requirement.

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 tool runs the repository pipeline and then applies its result in one call, distinguishing it from the separate stage tools. It names the sub-operations and explicitly contrasts with the individual pipeline/apply tools, so an agent can select it correctly.

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

Usage Guidelines5/5

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

Explicitly says when to use this tool vs the alternatives: 'Use the separate stage tools when you need to review the plan or simulation before anything is written.' This gives a clear when-not and implies this tool is for when no review is needed.

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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