lessons_query

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

No annotations are provided, so the description alone must disclose behavior. It adds the useful detail of 'stable ids for attribution', but it does not explicitly state whether the operation is read-only, how relevance is determined, or any limits or side effects. The description is brief and leaves significant behavioral assumptions (e.g., no mutation, but not 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 a single sentence with no redundant phrasing. It efficiently front-loads the purpose and a key output detail. While very short, it is not overly verbose, though it could arguably include more parameter context without sacrificing conciseness.

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?

With three parameters, no output schema, and no annotations, the description is insufficiently complete. It explains the basic purpose but fails to specify what the parameters do, what the response structure looks like, or any limitations. The tool's complexity is low, but the missing parameter and output details leave significant ambiguity for an agent deciding to invoke it.

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 does not mention any of the parameters (tags, limit, query) or explain their semantics. The description's 'search' implies a query parameter, but tags and limit are left unexplained, leaving the agent to guess how the parameters interact.

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 a specific action ('Search the lessons register') and the output ('return relevant lesson records with stable ids for attribution'). This distinguishes it from sibling tools like lessons_apply, lessons_candidate, and lessons_supersede, which imply different operations (applying, selecting candidates, superseding).

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 implies that this tool is for searching lesson records, but it does not explicitly state when to use it instead of the sibling tools, nor does it mention any exclusions or prerequisites. The usage context is clear from the verb 'Search' but lacks explicit alternatives or when-not-to-use guidance.

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