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

Annotations provide no safety hints beyond destructiveHint=false, so the description carries the burden. It adds a key behavioral trait: if estimated_impact_usd is not provided, a default is calculated from severity. This goes beyond the schema and is valuable for understanding tool 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 three sentences, front-loaded with the core action. The second sentence provides concrete examples, and the third covers an important behavioral detail. Every sentence earns its place, and there is no fluff or redundancy.

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?

With an output schema present, return values need not be described. The description covers purpose, examples, and a important default-calculation behavior. It is complete enough for the AI agent to select and invoke the tool correctly, and it fits well among many logging siblings.

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?

Schema coverage is 100%, so baseline is 3. The description adds semantic value by explaining the meaning and default behavior of estimated_impact_usd, and by giving concrete examples for risk_type. This enriches the schema descriptions rather than merely repeating them.

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 starts with a specific verb and resource: 'Log a risk event that was blocked or avoided by the governance layer.' It clearly distinguishes this tool from general logging tools like thinkneo_log_event or thinkneo_log_decision by focusing on risk events and avoided impact. The examples further clarify the exact scope.

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 gives explicit context: use this when logging a risk event that was blocked or avoided, such as PII leaks or prompt injections. It does not explicitly name alternatives or say when not to use it, but the specificity of 'risk event' and the governance layer context provides clear guidance.

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