Record a reviewer verdict

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

Annotations provide idempotentHint and readOnlyHint, but the description adds critical behavioral details: writes to .diffgate/learnings.json, the specific effects of 'dismiss' (suppressing future flags) and 'confirm' (marking as real). No contradictions with annotations.

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?

Two sentences, no fluff. The first sentence states the purpose, the second clarifies verdicts and storage location. Ideal length and structure.

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?

Given the tool's complexity (6 params, 3 required) and the existence of an output schema, the description covers the core behavior (learning, storage, verdict effects). No missing context needed for correct invocation.

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 does not add per-parameter details but provides context about verdict's role. It does not significantly enhance understanding of parameters beyond the 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 uses specific verbs ('Record', 'suppresses', 'marks') and specifies the resource (reviewer's verdict on a finding). It clearly distinguishes from sibling tools by focusing on feedback/learning rather than analysis, capabilities, or checking.

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 implies the context (after a review, to suppress noise or confirm findings) but does not explicitly state when not to use this tool or contrast with siblings like diffgate_analyze or diffgate_explain.

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