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devkamani9313-lab

open-source-contribution-mcp-server

generate_code_fix

Generate a file-scoped diff fix for a GitHub issue, adhering to the target repository's coding conventions.

Instructions

Generate scoped, file-level diff fix for an issue adhering to target repo conventions

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYesTarget repository in "owner/repo" format
issueNumberYesTarget issue number
fixDescriptionYesDetailed description of the proposed code fix
targetFilePathYesFile path to be modified (e.g. "src/utils/parser.ts")
proposedChangesYesThe code fix diff or full replacement content
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It states that the tool 'generates' a diff fix, implying it does not apply changes, but it does not disclose output format, side effects, authentication needs, or whether it modifies any repository. This leaves significant behavioral aspects undisclosed.

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?

The description is a single, front-loaded sentence that gets straight to the point with a clear verb and resource. It contains no filler or redundant phrases, earning a perfect score for conciseness.

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

Completeness2/5

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

Despite having 5 parameters, no annotations, and no output schema, the description does not explain what the tool returns, how the parameters interrelate, or any prerequisites. It is a minimal purpose statement that leaves significant contextual gaps for a tool of this complexity.

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?

The schema descriptions already cover 100% of parameters, so the baseline is 3. The description adds the qualifiers 'scoped' and 'adhering to target repo conventions', which informally relate to the 'proposedChanges' and 'targetFilePath' parameters, but it does not provide additional structural or formatting details beyond what the schema already states.

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 explicitly states the tool's main action: 'Generate scoped, file-level diff fix for an issue'. It clearly identifies the resource (an issue) and the output (a diff fix), and distinguishes this from sibling tools like 'generate_unit_tests' or 'submit_pull_request' by focusing on code fixes.

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

Usage Guidelines2/5

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

The description offers no explicit guidance on when to use this tool versus alternatives. It does not mention scenarios where it should or should not be used, nor does it reference any sibling tools. The only context is the purpose itself, which is insufficient for an agent to decide between this and related tools like 'generate_unit_tests' or 'submit_pull_request'.

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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