Search all documentation sections for a keyword or phrase.
Returns up to 5 matches as {section_id, title, snippet}, best match first.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It discloses the output shape (section_id, title, snippet), a limit of up to 5 results, and that results are ordered by best match first. This provides meaningful transparency beyond a basic statement, though it does not detail matching algorithms or edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first directly states the action, the second describes the return output and limit. Every sentence contributes meaning with no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with an output schema, the description covers purpose, scope, return format, limit, and ordering. It does not mention edge cases like empty results or search semantics, but the provided details are sufficient for typical usage and align well with the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only defines query as a required string without a description. The description adds crucial meaning by stating it accepts a keyword or phrase, compensating for the 0% schema description coverage. It does not elaborate on matching rules (e.g., case sensitivity, partial matches), but offers essential context for the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches all documentation sections for a keyword or phrase, using a specific verb and resource. It distinguishes itself from siblings get_doc_section and list_doc_sections by focusing on keyword discovery across the entire documentation set.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies its use when searching across all documentation sections but does not explicitly compare to sibling tools or state when to use it over get_doc_section or list_doc_sections. No exclusions or alternatives are mentioned, leaving usage context somewhat implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool serves a distinct purpose: listing sections, retrieving one section by ID, and searching across sections. There is no functional overlap between get, list, and search, and the descriptions make the boundaries clear.
All tools follow a verb_noun pattern in snake_case (get, list, search). Minor inconsistency: search_docs uses 'docs' while the other two use 'doc_section(s)', but the pattern is predictable and readable.
With 3 tools, the set is minimal but well-scoped for a documentation browsing server. Each tool earns its place and covers the essential actions without unnecessary bloat.
The surface covers the full documentation lifecycle for readers: enumerate sections, retrieve specific sections, and search. There are no obvious dead ends or missing operations for the stated domain.