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GDM-Pixel

Stellaris MCP

by GDM-Pixel

search_docs

Search documentation using natural language queries to find relevant sections, file paths, and content.

Instructions

Semantic search in documentation and markdown files. Finds relevant documentation sections by natural language query. Returns file paths, section headings, and full content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language search query (e.g., "article publishing workflow", "release process")
limitNoMaximum number of results to return (default: 5)
Behavior3/5

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

With no annotations, the description must convey behavior fully. It states the tool returns specific information (file paths, headings, content) and implies read-only operation, but does not explicitly mention read-only, destructive potential, rate limits, or authorization requirements. The description is adequate but not comprehensive.

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 extremely concise, consisting of two sentences that immediately convey the tool's purpose and output. No redundant or irrelevant information is present, making it easy for an AI agent to quickly understand the tool.

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 only 2 parameters and no output schema or annotations, the description covers the essential aspects: purpose, type of content, and return values. It does not specify defaults (e.g., limit default) or edge cases, but for a search tool this is sufficient.

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

Parameters3/5

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

Schema coverage is 100% with clear parameter descriptions for 'query' and 'limit'. The tool description adds no extra parameter details beyond what the schema provides. Baseline 3 is appropriate as the description does not need to add much, but also does not enhance understanding of parameters.

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 defines the tool as performing semantic search on documentation and markdown files using natural language queries. It specifies the type of content searched and the return fields (file paths, section headings, full content), effectively distinguishing it from sibling tools like search_code and db_search.

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?

The description provides clear context by stating it searches 'documentation and markdown files', implying its use case compared to code or database search tools. However, it lacks explicit when-to-use or when-not-to-use guidance and does not name alternatives, which prevents a higher score.

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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