get_agent_expertise

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

The description implies this is a read-only operation by stating it 'shows' data, which is appropriate. However, with no annotations and no detail on side effects, rate limits, or authentication, the transparency is minimal.

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 very concise, with only two sentences plus an Args line. Every word adds value, and the structure is front-loaded with the core purpose.

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 tool with one required parameter and no output schema, the description is minimally adequate. It explains the return data (areas and scores) but could improve by clarifying what 'expertise scores' represent or any constraints.

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 description includes an 'Args' section but provides no explanation of the 'agent_id' parameter beyond its name. With 0% schema description coverage, the agent gains no additional meaning from the text.

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 retrieves an agent's expertise profile, including areas voted on and scores. However, it does not differentiate from siblings like 'get_consensus' or 'list_decisions', leaving potential confusion about when to use this tool.

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or exclusion criteria, leaving the agent without decision support.

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