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Search official agent docs

search_docs
Read-onlyIdempotent

Search the official documentation of Claude Code, Cursor, OpenAI Codex and MCP. Use it before answering any question about using, configuring or administering these products. Not for other products or general programming. If the answer could differ between products and the user hasn't said which one, ask.

Returns one passage per page, with the page's one-line description and a relevance score; under ~0.5 means the docs probably don't cover it. One topic per call: split multi-part questions. Need more than the passage? Call read_section(url), or read_section(url, heading) for one of the passage's other_sections.

Input Schema

NameRequiredDescriptionDefault
limitNoPages to return, 1-20 (default 8).
queryYesWhat to find, in English: keywords or a short question, e.g. "<product> <feature> <what you need>".
productNoOnly this product. Set it when the user has named the product, now or earlier in the conversation. Otherwise leave it empty: an unfiltered search still finds product-specific pages, while a wrong product hides the right ones.
response_formatNo`concise` (default): first 300 characters of each passage, enough to choose. `detailed`: full passages, about 800 tokens each. Start concise; re-run detailed with a small limit for the pages you need.concise

Output Schema

NameRequiredDescriptionDefault
passagesYesRanked documentation passages. Empty if nothing matched.
index_snapshotYesDate the documentation was indexed (ISO); null if unknown.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

With readOnly/idempotent already covered by annotations, the description adds genuinely new behavioral context: one passage per page, a relevance score with a ~0.5 signal threshold, and the one-topic-per-call constraint. These are operational traits not available in the schema or annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose and scope are front-loaded in the first two sentences, with return-shape and follow-up guidance after. It is denser than strictly necessary (the relevance-score aside could be trimmed), but every sentence carries actionable content.

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?

For a search tool with an output schema, the description covers scope, exclusion criteria, disambiguation, result shape, and the escalation path to read_section. An agent has everything needed to call it and interpret results without opening other fields.

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 coverage is 100%, so the baseline would be 3, but the description adds decision guidance beyond the field docs: set product only when the user has named it (a wrong product hides the right pages), and start concise / re-run detailed with a small limit. This meaningfully shapes parameter usage.

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?

States a specific verb+resource ('Search the official documentation') and enumerates the exact scope (Claude Code, Cursor, OpenAI Codex, MCP). It also carves itself away from the sibling read_section by naming it as the follow-up for full content.

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?

Explicit when-to-use ('before answering any question about using, configuring or administering these products'), explicit when-not ('Not for other products or general programming'), and an ambiguity rule ('If the answer could differ between products... ask'). It also routes to read_section for deeper content.

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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