assess_ai_risk

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

Despite no annotations, the description includes a comprehensive 'Behavioral Transparency' section covering side effects (read-only, no side effects), authentication (none for basic, API key for pro), rate limits (free 10/day, pro unlimited), error handling (structured errors), idempotency, and data privacy. This fully informs the agent of 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 (When to use, Behavioral Transparency). However, it contains repetition: the 'Behavior' paragraph and 'Behavioral Transparency' section both state read-only and stateless. This redundancy slightly reduces conciseness.

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 the tool's purpose, parameters, behavioral traits, and constraints extensively. It lacks precise output format details (e.g., expected JSON structure) but given no output schema, the general description is adequate. Missing api_key parameter description is a gap, but overall completeness is high.

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's Args section adds meaning for 5 of 6 parameters (system_description, system_name, risk_criteria, caller, tier), clarifying their roles. However, it omits the api_key parameter present in the schema. Given 0% schema coverage, the description partially compensates but misses one parameter.

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 'Perform ISO 42001 Annex B risk assessment for AI systems' and lists specific activities (risk criteria establishment, identification, analysis, evaluation). It clearly distinguishes from sibling tools like quick_scan or predict_risk_neural by focusing on comprehensive Annex B risk assessment.

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?

Provides a dedicated 'When to use' section listing use cases (assess, audit, verify compliance, gap analysis) and a 'When NOT to use' warning against substituting for legal counsel. This gives clear guidance on appropriate contexts.

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