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search_by_type

Search documents filtered by category like architecture, bugfixes, or tests to get precise results. Specify the document type and query to retrieve relevant chunks.

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
top_kNo
projectNo
doc_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden. It states 'Read-only, no side effects' and describes the return value as 'Ranked chunks... with source, relevance %, and text.' It does not detail error conditions or rate limits, but the core behavioral traits are well-covered.

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 paragraph but well-organized: opening summary, usage instructions, then a clear parameter list. Every sentence is informative and concise. No wasted words.

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 tool complexity (4 parameters, filtering, no annotations, has output schema), the description covers purpose, usage, parameters, and return value comprehensively. It mentions output format and differentiates from siblings. No critical information is missing.

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%, so the description must fully explain parameters. It does: query is 'Search query (natural language)', doc_type lists all allowed values, top_k explains default 5, and project is 'Target project name (optional)'. This adds meaning far beyond the bare 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 clearly states the tool searches documents filtered by a specific category ('Search filtered by a specific document category') and explicitly notes it is read-only with no side effects. It distinguishes itself from sibling tools like search_docs, search_bugfixes, and search_tests by describing when to use each.

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 provides explicit guidance: 'Use instead of search_docs() when you know the category' and mentions alternatives: 'Use search_bugfixes() or search_tests() as convenient shortcuts for those specific categories.' This clearly tells the agent when to use this tool vs others.

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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