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powmarx

pow-mcp-rag-new

by powmarx

search_specs

Search specification and documentation files to locate relevant content while filtering out source code. Retrieve specific spec sections for natural language queries.

Instructions

Search only specification and documentation files (filters out source code). Use when you need "what does the spec say about X" without code noise.

Args: query: Natural language search query project: Optional project name filter top_k: Number of results (default: 5, max: 20)

Returns: Relevant documentation chunks (specs, requirements, design docs, PDFs)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
top_kNo
projectNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that it filters out source code and returns 'relevant documentation chunks,' which is useful, but it omits behavioral details like whether search is semantic or keyword-based, whether prior indexing is required, or how ranking works. This is adequate but not rich.

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 well-structured with a purpose statement, usage hint, Args list, and Returns section. Every sentence earns its place, with no redundant or filler content.

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 the tool has 3 parameters and an output schema, the description covers purpose, usage, parameters, and return format adequately. It lacks some context such as prerequisite indexing or error scenarios, but these are not essential for basic invocation. Sibling differentiation is partially addressed but could be stronger.

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 fully compensates with an 'Args' section explaining each parameter: natural language query, optional project filter, and top_k with default and maximum. This adds meaning beyond the schema's bare titles and defaults, providing sufficient guidance for invocation.

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 a specific verb+resource: 'Search only specification and documentation files' with an explicit filter ('filters out source code'). This distinguishes it from sibling tools like search_code and search_docs by targeting a specific document scope.

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

Usage Guidelines4/5

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

Provides a clear use case: 'Use when you need "what does the spec say about X" without code noise.' This indicates when to use it and implies not using it for code, but it does not explicitly name or contrast with sibling tools such as search_docs, leaving some ambiguity for overlapping documentation searches.

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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