team_learn

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

Annotations are absent, so the description carries the behavioral burden. It discloses the author attribution requirement and the team_recall behavior. However, it does not mention if the operation is destructive, reversible, or requires special permissions. 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?

Two sentences, front-loaded with purpose and key differentiator. No wasted words.

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 10 parameters (5 required) and no output schema, the description covers the primary purpose and unique behavioral constraint (author attribution). Sufficient for a store operation, though could mention the outcome or recall integration briefly.

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 100%, so baseline is 3. The description adds emphasis on the 'author' parameter being required, but otherwise does not explain parameter meanings beyond what the schema provides.

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?

Clearly states the action ('Store a lesson'), the target ('shared team brain'), and the benefit ('all team members benefit'). Distinct from sibling 'learn_from_attempts' by highlighting the author requirement for attribution.

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 mentions when to use and contrasts with a sibling tool ('Like learn_from_attempts, but REQUIRES an author name'). Lacks explicit 'when not to use' or other alternatives, but the context is sufficient.

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