Search database schema

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

Annotations already provide readOnlyHint=true and openWorldHint=true, so the description's disclosure burden is lower. The description adds context about the Pinecone vector store and the first-step pipeline role, which is valuable beyond annotations.

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 sentences, no wasted words. The first sentence defines the tool, the second provides usage instruction. Front-loaded and efficient.

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, but the description indicates what is returned (relevant tables, columns, types, relationships). For a semantic search tool, this is sufficient. The tool is moderately complex (5 params, no nested objects) and the description covers its role adequately.

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 100%, so all 5 parameters are documented in the schema. The description reinforces the 'question' parameter by saying 'pass the user question verbatim' but does not add new semantics beyond what the schema provides for other parameters. Baseline 3 is appropriate.

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 it performs semantic search over the database schema stored in Pinecone, explicitly for text-to-SQL requests. It distinguishes from siblings by positioning itself as the first step and mentioning retrieval of tables, columns, types, and relationships.

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 explicitly says 'Call this FIRST for any text-to-SQL request', providing clear context for when to use. It doesn't explicitly exclude alternatives like get_table_schema or list_tables, but the 'first step' instruction implies the workflow.

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