ai_collection_info

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

No annotations are provided, so the description must carry the full burden. It indicates the tool returns information and hints at a cross-check feature, but does not explicitly state it is read-only, mention any side effects, auth requirements, or rate limits. It is adequate but not rich.

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 a single sentence that front-loads the main purpose and lists specific metrics. There is no wasted text, and it is appropriately concise.

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?

For a simple info tool, the description covers what data is returned. However, it lacks details on error handling, connection requirements, and does not compensate for the lack of parameter documentation. It is minimally complete but with gaps.

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?

The input schema has one parameter ('connection') with a default but no description. Schema coverage is 0%. The description does not explain the parameter or how to use it, leaving the agent without guidance on what 'connection' refers to.

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 returns info about a Qdrant collection, listing specific metrics (vector size, distance metric, point count, indexed-vectors count, plus Odoo-side count). It uses a specific verb 'Return info' and distinguishes from siblings like ai_list_documents which list documents, not collection metadata.

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, no prerequisites, and no context about when to call it. Given sibling tools like ai_search_similar or ai_pipeline_run, the tool's use case is implied but not explicitly stated.

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