Corpus Semantic Search

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

No annotations exist, so the description carries the full burden. It usefully discloses that results include glossary_terms (synonyms/concepts), which is real behavioral context, but says nothing about filtering behavior, what ray_only or include_extended do, or result ordering across 7 parameters.

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?

Two short sentences, front-loaded with the core mechanism and the key differentiator; nothing is padded. Slightly under-specified rather than wasteful.

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?

An output schema exists, so return values need not be explained, and the glossary_terms disclosure is a bonus. However, with 43% schema coverage and six undocumented filter/option parameters, the definition is not complete enough for an agent to use the full parameter surface confidently.

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 only 43%, and the description adds no parameter meaning at all — author, series, doc_type, and ray_only are undocumented in both places. Only limit, query, and include_extended have schema descriptions, so the description fails to compensate for the coverage gap.

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+resource (semantic/embedding search over the corpus) and clarifies the distinguishing mechanism — meaning-based matching rather than exact keywords. It does not name the keyword sibling (corpus_search) explicitly, so the differentiation is implied rather than routed.

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 clause 'even without exact keyword matches' implies when this tool is preferable to keyword search, but no alternative is named and no exclusions or prerequisites are given. Usage is inferable but not stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.