Search Shipshape Data's documentation: 169 practical guides on data and AI plus the service and industry pages. Results include the questions each page answers and its URL.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results, default 5 | |
| query | Yes | What you want to know, e.g. "what is data lineage" |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the bar is lower. The description adds useful behavioral context by specifying the result shape (questions each page answers and URL), which goes beyond what annotations provide.
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?
A single sentence that front-loads the action and scope, then concludes with the key result detail. No wasted words or repetition of schema or annotation information.
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 search tool with two well-documented parameters and read-only/idempotent annotations, the description covers the essential behavior and result contents. It could explain more about result ordering or how to use the returned URL, but it is adequate for correct selection and invocation.
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?
Schema coverage is 100%: both query and limit are fully described in the input schema. The description does not add parameter-level details beyond what the schema already provides, so a baseline score of 3 is appropriate.
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 identifies a specific verb ('Search') and a specific resource ('Shipshape Data's documentation'), and further narrows the scope to 169 guides plus service/industry pages. This distinguishes it from sibling tools like get_page and list_sections by action and purpose.
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 search_docs is for finding documentation content, but it does not explicitly say when to use it over get_page or list_sections. There is no exclusion or alternative guidance, only a clear statement of what the tool 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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Each tool serves a clearly distinct purpose: search_docs finds relevant content, list_sections provides structural orientation, and get_page retrieves a specific page's content. There is no meaningful overlap or ambiguity between them.
All tool names follow a consistent verb_noun pattern: get_page, list_sections, search_docs. The naming is uniform, predictable, and immediately conveys each tool's action.
Three tools are well-scoped for a documentation-oriented server. Each tool covers a distinct need—searching, exploring structure, and retrieving content—without redundancy or unnecessary bloat.
The tool set provides full coverage for navigating and consuming documentation: discover via search, orient via section listings, and retrieve via page fetch. No obvious gaps or dead ends exist for the stated purpose.