Find test gaps

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

Annotations already declare a safe read (readOnlyHint=true, destructiveHint=false), so the description's added value is the risk model definition (Probability × Impact × DetectionDifficulty) and the explicit invariant that risk never alters coverage/proof status — non-obvious behavior an agent could otherwise misread as a status mutation. It does not mention result ordering or pagination 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?

Two sentences, front-loaded with what is returned, then the ranking rule and the invariant. Every clause carries information and nothing is padded.

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 no output schema, the description does the necessary work by naming both return sections and the ranking basis, which is enough to interpret results. Minor gaps remain: it does not describe the shape of an individual gap entry or whether requirement gaps are also ranked.

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 limit, workspace, and min_priority are already documented with defaults and ranges. The description adds no further meaning about the parameters, so the baseline of 3 applies.

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?

States a specific verb and two concrete resources: requirements/flows with weak or missing test evidence, plus 'top_risk_gaps' for unproven code symbols. The named output bucket and the risk-ranking criterion make it clearly distinct from siblings like orangepro_rtm or orangepro_graph_score.

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?

Usage is only implied: the description tells you what you get, from which an agent can infer this is the gap-discovery/prioritization step, but it never says when to call it versus orangepro_rtm, orangepro_stats, or orangepro_generate_tests. The closing caveat about risk not changing proof status is a helpful semantic guardrail rather than routing guidance.

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