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

The description adds behavioral context beyond the annotations by stating inputs are validated server-side and the output is a 'structured, audited deliverable'. However, it doesn't disclose what happens on validation failure, rate limits, or specific output structure. The readOnlyHint annotation already covers safety, so this is adequate but not rich.

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 concise at three sentences and front-loaded with the tool's purpose. The 'Gapup agent-payable C-suite expertise (COO)' phrase is marketing fluff and the Buffer reference case is illustrative but non-essential. Overall, it is efficient without being overly terse.

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?

For a tool with complex nested inputs and no output schema, the description is incomplete. It mentions a structured deliverable but doesn't describe its contents, how to interpret results, or the required fields beyond a vague reference to 'case fields'. The Buffer case gives a concrete example but doesn't suffice for operational completeness.

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 schema description coverage at only 20%, the description needed to compensate for the many undocumented parameters (company, signals, employees, focus). It merely says 'send the documented case fields' without explaining what fields are expected or how they map to the schema. This adds minimal value beyond the raw schema.

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 states the tool is an 'anti-attrition shield' and references 'detection des at-risk parmi 80 FTEs', clearly indicating it detects employees at risk of leaving. However, the main verb is 'Returns' rather than a direct action verb like 'detect' or 'assess', and it doesn't differentiate from sibling tools like churn_defender or enps_auto.

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?

No guidance is provided on when to use this tool versus alternatives. The only directive is 'send the documented case fields', which is about input submission, not usage context. There are no exclusions or comparisons to related tools.

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