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write_best_practice

Write a best practice guide, index it in a vector store, and push to git—capturing team rules and conventions for recurring code patterns.

Instructions

Create a coding standard or best practice document, index it, and auto-push.

    Side effects: creates best-practices/{slug}.md in the docs path,
    indexes it into the vector store, and pushes to git if configured.
    Overwrites an existing file with the same title.

    Use for recurring patterns, conventions, and rules the team should follow.
    Use write_architecture_doc() for system-level decisions,
    write_bugfix_summary() after fixing a specific bug.

    Args:
        title: Short title (e.g. "Error Handling in API Routes")
        context: When and where this practice applies
        rule: The actual rule or pattern to follow (be specific)
        rationale: Why this rule exists and what problems it prevents
        examples: Code examples showing correct vs incorrect usage (optional)
        project: Target project name (optional)

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ruleYes
titleYes
contextYes
projectNo
examplesNo
rationaleYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses side effects (creates file, indexes, pushes to git, overwrites existing). However, it omits details about authorization needs, error handling, or what happens if auto-push fails.

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 well-structured with a summary, side effects, usage guidelines, and args list. It is concise but could be slightly tighter (e.g., 'Args:' could be merged with the preceding list). Overall, every sentence adds value.

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 6 parameters (4 required), the presence of an output schema, and no nested objects, the description covers purpose, side effects, usage, and args. It lacks details on input format specifics (e.g., is markdown expected?) but is otherwise complete for an agent to use the tool effectively.

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?

The schema has no descriptions for any parameters (0% coverage). The description compensates by explaining each parameter in plain English: title, context, rule, rationale, examples, project. This adds semantic meaning beyond the schema's type/title information.

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 uses a specific verb-resource combination: 'Create a coding standard or best practice document, index it, and auto-push.' It clearly identifies the tool's purpose and distinguishes it from sibling tools like write_architecture_doc and write_bugfix_summary.

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 explicitly states when to use this tool ('Use for recurring patterns, conventions, and rules the team should follow') and provides concrete alternatives for other scenarios ('Use write_architecture_doc() for system-level decisions, write_bugfix_summary() after fixing a specific bug').

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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