search_semantic

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

Annotations already declare readOnlyHint=true and idempotentHint=false. The description adds the embedding model and an important coverage caveat ('FCC filings have limited embedding coverage'), which is real behavioral context beyond annotations. Missing return-format/ordering details keeps it from a 5.

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?

Three tightly packed sentences, front-loaded with the core purpose and ending with the practical FCC caveat. No redundant restatement of the title or schema.

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?

No output schema exists, and the description reasonably covers what the tool does, the embedding basis, and a key coverage limitation. An agent has enough to call it correctly; only minor gaps (result ordering, similarity semantics) remain and are largely covered by schema.

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 all six parameters (query, limit, agency, dates, min_similarity) are already documented in structured form. The description adds only that queries are natural language, not syntax or defaults beyond the schema, so baseline 3 applies.

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 vector search across filing text') and the mechanism ('nomic-embed-text-v1.5 embeddings ... by meaning, not just keywords'). This clearly distinguishes it from the sibling search_filings keyword tool, which is named explicitly.

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?

Gives clear when-to-use context (natural-language semantic matching vs keywords) and names the alternative for FCC keyword search. It stops short of explicit when-not guidance for other agencies or datasets, but the routing to search_filings is concrete.

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