explain_decision

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

Description fully compensates for missing annotations by detailing behavior: no side effects, deterministic output, rate limits (free/pro tiers), and authentication needs. Contradiction is false.

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?

Well-structured: summary line, Args, Behavior, usage sections. Every sentence adds value; no wasted words. Appropriate length.

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?

Covers purpose, parameters, behavior, and usage guidelines. Lacks explicit output format description; mentions 'structured output' but could clarify whether it's text or JSON. No output schema provided.

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?

With 0% schema coverage, description explains each parameter: 'decision' (the AI decision), 'factors' (comma-separated, optional for generic), and 'api_key' (optional for pro tier). Adds critical meaning beyond schema titles and types.

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?

Description states 'Generate a human-readable explanation of an AI decision', which is a specific verb and resource. It clearly distinguishes from siblings like create_impact_assessment or generate_model_card.

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?

Includes explicit 'When to use' and 'When NOT to use' sections, providing context for when the tool is appropriate. However, the 'When to use' description is somewhat generic and does not directly compare to sibling tools.

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