Search Collection

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

Annotations already declare readOnlyHint and idempotentHint, so the description adds value by disclosing that the operation is 'Free — no credits consumed' and that async indexing must complete before results appear. This clarifies real-world behavior beyond the safety hints.

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 well-structured with clear sections: purpose, usage guidance, prerequisite, return format, and example prompts. It is front-loaded with the main purpose and includes no filler. Every sentence contributes to understanding the tool.

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?

The description covers all necessary context: purpose, usage, prerequisites, return format, cost, and examples. Given the tool's moderate complexity and the presence of an output schema, this is fully self-contained and leaves no major gaps for an agent to misuse.

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 parameters (collection_id, query, limit) are already documented with descriptions and examples. The description adds example prompts that illustrate query phrasing but does not change the fundamental meaning of any parameter. 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 'Semantic (vector) search across documents in a collection' with a specific verb (search) and resource (documents in a collection). It also distinguishes itself from sibling tool collection.ask, which provides synthesized answers rather than raw chunks.

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?

Explicitly states when to use: 'Use when you need raw matching chunks from a collection.' Directly names the alternative: 'For a synthesized cited answer from the same context, use collection.ask instead.' Also provides a prerequisite about indexing completion and polling job.status.

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