refine_agent

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It only states that changes are recorded but does not mention side effects, idempotency, permissions, or whether previous versions are overwritten.

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 moderately concise with a clear structure using an English explanation and a bilingual Args list. The poetic lines add some verbosity but do not detract significantly. It is front-loaded with the main 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?

The description covers purpose and parameters adequately, and an output schema exists (so return value details are not needed). However, due to the lack of annotations, more behavioral context (e.g., side effects, safety) is needed for a mutation tool.

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 0% description coverage, but the description's Args section adds meaningful context for all three parameters: agent_id (source from forge_agent), changes (description of changes), refiner (who refined, defaults to creator). This fully compensates for the schema gap.

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 verb 'refine' or 'optimize' and the resource 'existing AI Agent'. It distinguishes from sibling tools like forge_agent (creation) by specifying it's for improvements. The poetic lines reinforce the concept of refinement.

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 usage for improving existing agents, and the Args section clarifies key parameters. However, it lacks explicit guidance on when to use this tool vs alternatives (e.g., forge_agent for new agents) or when not to use it.

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