submit_feedback

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

With no annotations, the description bears full responsibility. It discloses the event type (kind 7000), idempotency on (job_event_id, rating), and suggests a follow-up action. No contradictions.

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 two sentences with a third recommendation sentence. It is front-loaded, concise, and every sentence adds essential information without fluff.

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 simple tool with 3 params and no output schema, the description covers purpose, behavior (idempotent), and follow-up. It could mention response format but is largely complete given the tool's simplicity.

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 67% (2 of 3 params have descriptions). The description adds value by explaining idempotency ties job_event_id and rating, and clarifies provider_npub's optionality based on context, going 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 clearly states 'Rate a completed job' and explains it mirrors web app buttons, publishing a NIP-90 kind 7000 feedback event. It distinguishes from sibling tools like submit_diff_review by specifying the feedback mechanism.

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 provides clear context: use after a completed job, and mentions idempotency and when to call add_contact. It lacks explicit exclusions but covers key usage scenarios well.

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