Skip to main content
Glama

write_bugfix_summary

Record bug fixes with root cause, solution, and lesson learned. Saves and indexes a markdown file, then pushes to git to prevent repeated mistakes.

Instructions

Create a bugfix summary .md file, index it immediately, and auto-push to git.

    MANDATORY after every bug fix — these summaries are retrieved during
    future debugging sessions to avoid repeating the same mistakes.

    Side effects: creates bugfix-log/YYYY-MM-DD-{slug}.md in the knowledge
    repo docs path, indexes it into the vector store, and pushes to the
    remote git repo if MCP_GIT_REPO_URL is configured. Overwrites an
    existing file if the same title is used on the same day.

    Use write_architecture_doc() for design decisions,
    write_best_practice() for recurring patterns.

    Args:
        title: Short, descriptive title of the bug (used in filename)
        root_cause: What was the actual cause? (be technical)
        solution: How was it fixed? (describe code changes made)
        lesson_learned: What should be done differently next time?
        affected_files: Comma-separated list of changed files (optional)
        tags: Comma-separated categories, e.g. "auth,race-condition,critical" (optional)
        project: Target project name (optional)

    Returns:
        Saved filename, chunk count, and whether auto-push succeeded.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNo
titleYes
projectNo
solutionYes
root_causeYes
affected_filesNo
lesson_learnedYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations are not provided, but the description details all side effects: creates file in bugfix-log/, indexes into vector store, pushes to remote git, and overwrites if same title same day. Discloses dependencies on MCP_GIT_REPO_URL. No contradictions.

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?

The description is front-loaded with the core action and mandatory status. It includes side effects, alternatives, and parameter details. While slightly long, every sentence adds value, so it's efficient.

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

Completeness5/5

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

The tool has 7 parameters (4 required) and no output schema annotations, but the description covers the return format ('Saved filename, chunk count, and whether auto-push succeeded'). Combined with behavioral and usage details, it is fully complete for an agent to invoke correctly.

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

Parameters5/5

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

Schema description coverage is 0%, but the description includes an Args section with meaningful explanations for each parameter (e.g., title used in filename, root_cause: 'be technical', solution: 'describe code changes'). This adds significant value beyond the schema.

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 'Create a bugfix summary .md file, index it immediately, and auto-push to git.' It clearly specifies the verb (create) and resource (bugfix summary file), and differentiates from siblings like write_architecture_doc and write_best_practice.

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?

The description declares 'MANDATORY after every bug fix' and provides explicit alternatives: 'Use write_architecture_doc() for design decisions, write_best_practice() for recurring patterns.' This gives clear when-to-use and when-not-to-use guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/dl4rce/flaiwheel'

If you have feedback or need assistance with the MCP directory API, please join our Discord server