query-literature

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

No annotations are provided, and the description does not disclose behavioral traits such as whether the tool is read-only, destructive, or requires authentication. The SQL query nature implies read access, but this is not explicitly stated.

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 overly long (listing all 70+ table headers) and not front-loaded effectively. While informative, it could summarize the table structure more concisely without sacrificing essential details.

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 single parameter and no output schema, the description adequately covers the table schema needed for querying. However, it lacks usage guidelines and behavioral transparency, which are important for complete 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?

While the schema already describes the 'sql_query' parameter, the description adds significant value by detailing the entire table structure (headers, rows, descriptions). This helps agents formulate precise queries, compensating for the minimal parameter description in the schema.

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 states 'Query an SQL database for structured summaries of studies' which clearly indicates the tool's function (querying literature data). It distinguishes from siblings like 'get-raw-data' which focus on raw observation data. However, it could be more specific about the type of literature (e.g., phenology studies).

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 provides no guidance on when to use this tool versus alternatives like 'export-raw-data' or 'observation-comment'. It does not specify when not to use it or mention any prerequisites.

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