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search_by_type

Retrieve documents filtered by a specific category like architecture or bugfix, improving search precision by narrowing results to the selected type.

Instructions

Search filtered by a specific document category. Read-only, no side effects.

    Use instead of search_docs() when you know the category — it improves
    precision by restricting results to that type only.
    Use search_bugfixes() or search_tests() as convenient shortcuts for
    those specific categories.

    Args:
        query: Search query (natural language)
        doc_type: Category filter — one of: "architecture", "api",
                  "bugfix", "best-practice", "setup", "changelog",
                  "test", "readme", "docs"
        top_k: Number of results (default: 5)
        project: Target project name (optional)

    Returns:
        Ranked chunks of the specified type with source, relevance %, and text.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
doc_typeYes
top_kNo
projectNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

The description states 'Read-only, no side effects' upfront, which is a clear behavioral trait. No annotations present, so description carries the full burden; it adequately covers safety but lacks details on rate limits or pagination, though not critical for this tool.

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?

Description is brief yet comprehensive, with a clear top-level purpose followed by usage guidance, parameter descriptions, and return format. No wasted words; each sentence adds value.

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?

Given the presence of an output schema and the tool's simple nature (4 params, 2 required, no nested objects), the description fully explains all necessary aspects: purpose, usage, parameters, and return format.

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 has 0% description coverage, but description adds meaning: query is natural language, doc_type lists all 9 allowed values, top_k defaults to 5, project is optional. This compensates well for the missing schema descriptions, but could be improved by structuring the enum values officially.

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?

Clearly states 'Search filtered by a specific document category', specifying verb and resource. Distinguishes from sibling tools like search_docs, search_bugfixes, and search_tests by mentioning they are alternatives for specific categories.

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 'Use instead of search_docs() when you know the category' and points to search_bugfixes/search_tests as shortcuts. Provides clear when-to-use guidance.

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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