search_vector_db

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

With no annotations provided, the description carries the burden of disclosing behavior. It explains the mechanism (embedding generation, Azure AI Search index) which adds useful context about backend behavior. However, it doesn't disclose details like rate limits, authentication expectations, or behavior when no matches are found.

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 efficient: a two-sentence first line plus a brief paragraph explaining the mechanism. No wasted words, front-loaded with the core purpose. Could arguably be trimmed but stays within reasonable bounds.

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?

Given the output schema exists (so return format is documented elsewhere) and schema coverage is complete, the description is reasonably complete. It explains the query mechanism and result source. For a simple 2-parameter search tool with an output schema, the description provides sufficient operational context.

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 schema already documents both parameters well. The description adds the context that 'query' gets embedded, which is a slight enhancement, but top_k semantics are already fully covered by the schema description. Baseline 3 is appropriate since schema handles parameter documentation.

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 states the tool searches a vector database using semantic similarity, specifying it generates embeddings and queries Azure AI Search. It clearly identifies the tool as the search counterpart to its sibling 'search_add_to_vector_db', though it doesn't explicitly contrast itself with that sibling.

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 gives context on what the tool does (semantic search over project vector DB) which implicitly suggests when to use it. However, it doesn't explicitly state when NOT to use it or offer alternatives among siblings (e.g., contrast with search_add_to_vector_db which is for adding, not searching).

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