generate_explanation

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

No annotations are present, so the description carries full burden. It does not disclose whether generation triggers a computation, requires authentication, modifies state, or has side effects. For a generation tool, the agent needs to know if it is a read-only operation and its resource intensity.

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 wasted words. It is appropriately concise, though it could benefit from a brief note on usage context while remaining efficient.

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 tool with three required parameters and no output schema or annotations, the description is minimal. It does not explain the nature of the explanation (e.g., text output, confidence scores), error conditions, or any prerequisites. The agent lacks sufficient context to reliably invoke the 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 covers all three parameters with descriptions (coverage 100%), so the description need not add much. It adds no additional meaning beyond the schema. According to guidelines, baseline is 3 when schema coverage is high.

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 action (generate) and resource (explanation for a specific feature in AI model). However, it does not differentiate from sibling tools like search_explanations, which might retrieve existing explanations. The purpose is clear but lacks sibling differentiation.

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. Sibling tools like search_explanations, get_activations, or search_top_features exist, but the description does not contextualize when generation is appropriate versus searching or retrieving activations.

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