corpus_suggestSuggest terms and document IDs from partial queries to complete searches in the Ray Peat corpus and WikiPeatia wiki.
Corpus autocomplete: term and document (doc_id) suggestions.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Partial query (e.g. 'thyr', 'aspir') |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral disclosure burden. It does not state whether the operation is read-only, how many suggestions are returned, ranking behavior, permissions, or rate limits; it only says that suggestions are produced.
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 a single front-loaded sentence with no wasted words. It immediately communicates the tool's core function.
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 low-complexity, one-parameter tool with an output schema, the description covers the basic purpose. However, it omits usage guidance and behavioral context, which are especially important since no annotations are available.
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 description coverage is 100%, so the single query parameter is already well documented with examples. The description adds that suggestions can be terms or document IDs, but does not add further meaning to the query parameter itself.
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?
States a specific verb and resource: corpus autocomplete for term and document (doc_id) suggestions. It is clear enough to distinguish the tool from full search tools, but it does not explicitly differentiate itself from sibling suggest/search tools such as wiki_suggest or corpus_search.
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 term 'autocomplete' implies usage with a partial query, and the schema example reinforces that context. However, there is no explicit guidance on when to use this versus corpus_search, corpus_semantic_search, or other suggestion tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.