mitigation_recommendations

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

With no annotations, the description fully covers behavioral traits: states read-only, stateless, idempotent, no side effects, authentication details, rate limits, error handling, and data privacy. This is exceptionally thorough and leaves no ambiguity about the tool's behavior.

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 well-structured with clear sections but is longer than necessary. There is redundancy between the 'Behavior' section and the 'Behavioral Transparency' subsection, both reiterating idempotency and rate limits. Some sentences could be consolidated without losing clarity.

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 tool has 2 parameters, no annotations, and no output schema. The description covers purpose, parameters, usage guidance, and behavioral transparency comprehensively. The only gap is the lack of detail about the success output format (e.g., structure of remediation steps), but the overall context is sufficient for most use cases.

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 schema has 0% description coverage, but the 'Args' section compensates fully: it lists bias_type with all eight valid options and explains api_key as optional for pro tier. This adds essential meaning beyond the schema's type-only definitions.

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 explicitly states the tool's purpose: 'Get detailed remediation steps for a specific type of AI bias.' It lists the bias_type options, which clarifies the scope. However, it does not explicitly differentiate from sibling tools (e.g., detect_bias, fairness_metrics), though the verb 'remediation' and focus on steps implicitly distinguishes it.

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 includes dedicated 'When to use' and 'When NOT to use' sections, providing clear application contexts like compliance audits and gap analysis. It also cautions against using it as legal counsel. However, it does not explicitly compare with sibling tools or explain when to choose this tool over others.

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