create_impact_assessment

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

The description explicitly states the tool generates structured output without modifying external systems, has deterministic output for identical inputs, and no side effects. It also notes no authentication required for basic usage. This is comprehensive behavioral disclosure.

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 and bullet points, making it easy to read. While informative, it could be slightly more concise (e.g., merging the behavior section lines), but overall it earns its 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?

The description covers purpose, usage, parameters, and behavior. It mentions output is a template but does not specify the exact structure or format. Given no output schema, a bit more detail on output would improve completeness, but it is still adequate.

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?

Despite 0% schema description coverage, the description explains each parameter: system_name as 'Name of the AI system', affected_groups with example and default behavior, api_key as optional for pro tier. This fully compensates for missing schema descriptions.

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 it generates a DPIA/AIIA template for an AI system. It names the specific output type and lists parameters. It distinguishes from sibling tools (explain_decision, generate_model_card, quick_scan, transparency_audit) by focusing on impact 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?

The description provides explicit 'When to use' and 'When NOT to use' sections, guiding the agent on appropriate contexts. It also mentions rate limits (free tier: 10/day, pro tier: unlimited) and authentication requirements, giving clear usage boundaries.

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