semantic_search

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the native retrieve_text preference and SQL fallback plus semantic-identity provenance, but it omits permissions, expected return shape, error behavior, and performance/limits.

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 definition is compact and front-loads the core purpose before implementation detail. The second sentence is dense but earns its place by explaining the execution path, though jargon like 'semantic-identity provenance' is not unpacked.

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 an 8-parameter tool with no annotations, no output schema, and low schema description coverage, the description is not complete enough. It explains the search mode but not most parameter meanings or the result behavior an agent would need to invoke it 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 description coverage is only 25%, so the description must compensate. It mentions the query string and embedding column/ANN index, but it leaves many parameters such as k, table, projection, and exact_rerank without added semantic meaning.

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 gives a specific verb and resource: dense ANN semantic search using a query string. It also states key prerequisites (embedding column and ANN index), but it does not explicitly distinguish this tool from alternatives such as execute_sql or install_dense_ann beyond implying infrastructure requirements.

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?

It names prerequisites and describes an implementation preference/fallback, which implies when the tool is usable. However, it does not explicitly say when to choose it over siblings, what to do if the ANN index is missing, or when not to use it.

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