ecosystem_deep_review_cancel

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

No annotations provided, but the description fully discloses behavioral traits: it advances stage_status to shallow_failed, derives status to failed, adds a cancellation note, and explains sub-agent behavior. This covers all necessary transparency beyond what annotations would provide.

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?

Description is brief (4 lines), front-loaded with the primary action, and every sentence adds value (state condition, effects, sub-agent behavior). No unnecessary words.

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?

Input schema is simple and fully covered. An output schema exists (per context) but is not shown; per rules, description need not explain return values. The description covers the cancellation flow adequately. Minor gap: could mention if any side effects, but sufficient for a cancel action.

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 has one parameter (deep_review_id) with full description, so schema coverage is 100%. The description does not add semantic detail beyond 'EcosystemDeepReview.id', which is already in the schema. Baseline 3 is appropriate.

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?

Description clearly states the tool cancels an in-flight deep-review (stage_status='queued'), using a specific verb and resource. It distinguishes from sibling tools like ecosystem_deep_review_request and ecosystem_deep_review_status.

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 specifies the condition for use (stage_status='queued'), providing clear context. Does not explicitly state when not to use or name alternatives, but the condition is sufficiently clear.

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