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SARAN-KUMAR-S

DOC-Intelligence-MCP-SERVER

get_docs

Search official documentation for libraries like uv, OpenAI, LangChain, and LlamaIndex to answer developer queries.

Instructions

Search the latest official documentation to answer developer queries. Use this tool whenever the user asks questions about uv, openai, langchain, or llama-index.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe search terms or query (e.g. "How to use publish a package with uv on gitlab")
libraryYesThe specific library/technology to search for.
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'Search the latest official documentation' but fails to disclose important traits such as result format, pagination, caching behavior, or error handling. For a search tool, this is a significant gap.

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?

Two sentences, both front-loaded. The first sentence states purpose, the second gives usage guidance. No unnecessary words. Perfectly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple with two parameters and no output schema. The description covers purpose and when to use, but lacks details on return format, output behavior, or any limitations. Without output schema, the description should hint at what the agent can expect. It falls short, though the core use is conveyed.

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 description coverage is 100%, with both parameters described in the input schema. The description adds minimal extra meaning beyond the schema—it reiterates the library list and the query's purpose. Baseline is 3 for high coverage; the description does not provide substantial additional semantics.

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 'Search the latest official documentation to answer developer queries,' specifying the verb (search) and resource (latest official documentation). It explicitly lists the four libraries, making the tool's domain unambiguous. No siblings exist, so no differentiation needed.

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 explicitly states when to use the tool: 'Use this tool whenever the user asks questions about uv, openai, langchain, or llama-index.' This provides clear usage context, though it does not mention when not to use or alternatives. Given the absence of sibling tools, this is sufficient.

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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