ami_write_findings

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

With no annotations, the description carries the behavioral burden, and it does so well: it discloses what the server computes vs. what the agent supplies, and imposes a grounding constraint ('Ground every sentence in the run's own evidence; do not invent industry context'). That is exactly the kind of non-obvious behavior an agent needs to know.

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?

Three sentences, each earning its place: purpose, prerequisite, and grounding constraint. Front-loaded and no filler.

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 write tool with no annotations and no output schema, it explains the division of labor, the prerequisite read, and the evidence constraint. It doesn't mention failure modes or confirmation, but the essentials are covered.

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 description coverage is 100%, so the baseline is 3. The description adds the concept of narration_brief.sections_awaiting_you but not per-parameter nuance; it does not describe how the five optional fields map to those sections. Schema handles the individual parameters.

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 a specific verb and resource: 'Write the judgement sections of a run's scorecard.' It clearly distinguishes these from server-computed numbers and sections, and it names the exact prerequisite call (ami_get_scorecard). This makes the tool's purpose unmistakable and distinct from sibling tools like ami_get_scorecard.

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?

Explicitly instructs the agent to call ami_get_scorecard first and use narration_brief.sections_awaiting_you, which gives clear context for when to use this tool. It does not explicitly list when not to use it or name alternative tools, but the prerequisite and task boundary are clear enough.

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