team_learn

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

No annotations are provided, so the description must cover behavioral traits. It mentions that the lesson shows up in 'team_recall' with author attribution, adding some transparency. However, it does not disclose whether the tool overwrites existing lessons, its idempotency, error handling, or rate limits.

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 consists of two short, front-loaded sentences with no wasted words. It efficiently conveys the purpose and key distinction.

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 tool has 10 parameters (5 required) and no output schema, the description is brief. It provides high-level context but lacks details on the storage behavior, confirmation, or error handling. Completeness is adequate but could be improved.

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 reinforces the requirement of the 'author' parameter and adds context about its role in attribution. However, it does not provide additional semantics beyond what the schema already provides for other parameters.

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 stores a lesson in a shared team brain, using the verb 'store' and specifying the resource. It distinguishes itself from the sibling tool 'learn_from_attempts' by emphasizing the requirement of an author name 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?

The description explicitly compares the tool to 'learn_from_attempts' and highlights the need for an author name, providing clear context for when to use this tool (when team attribution is required). However, it does not specify exclusions or alternative use cases beyond that comparison.

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