search_content

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals default search scope (workbooks, published datasources, database tables), optional `types` filtering, grouping of matches by type, client-side pagination with a ~1200 item scanning limit per type, and the presence of a `note` field indicating this limitation. This goes beyond the schema and makes hidden behaviors explicit.

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 compact yet information-dense, front-loading the core purpose in the first sentence. Every subsequent sentence adds essential detail—usage context, defaults, side effects, and alternatives—without redundancy or padding.

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 structure need not be spelled out), the description covers all invocation-relevant aspects: what it searches, how to narrow results, how results are organized, pagination limitations, and when to choose an alternative. It is complete for an agent to select and call the tool correctly.

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 0%, so the description must compensate. It fully explains both parameters: `term` as a case-insensitive substring matched against the NAME field, and `types` with the allowed values (workbook, datasource, table, field, column) and default behavior when not passed. This adds all necessary meaning beyond the bare 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 uses a specific verb ('Find') and resource ('content whose NAME contains `term`') and clarifies it performs a case-insensitive substring match. It also distinguishes this tool from siblings by stating that every other tool and the Metadata API filter are exact-match, making its purpose and scope immediately clear.

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 states when to use this tool ('Use this when you only know part of a name') and contrasts it with alternatives, saying to prefer `graphql_query` or `where_used` once the exact name is known. This provides clear decision guidance for the agent.

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