close_feedback_loop

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It thoroughly explains the tool's behavior: it pulls open feedback, matches changes, resolves items with explanations, and notifies stakeholders via email with an exact summary. It also reveals the stakeholder-facing outcome ('The stakeholder sees exactly what happened to their feedback'). This goes well beyond a simple action verb and covers side effects, making it highly transparent.

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 appropriately sized for the tool's complexity. It uses a bold imperative for when to call, a concise flow list, and a stakeholder impact statement. Every sentence earns its place—no fluff or redundancy. The numbered flow improves scannability without wasting 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?

Given the tool has 3 parameters, no output schema, and no annotations, the description is remarkably complete. It covers the full workflow, the input expectations (open feedback, resolutions), the side effect (stakeholder notification), and even provides format examples. There is no obvious missing context that would prevent an agent from selecting and invoking this tool correctly.

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?

The schema already covers all parameters (100% coverage), but the description adds meaningful context: it explains that deploy_url is included in the notification, and it gives specific guidance on writing the note for resolutions ('Be specific: 'Nav restructured to separate admin and user flows' not 'Fixed the navigation''). This enriches the meaning of the resolutions parameter beyond the schema description, justifying a score above the baseline.

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 opens with a specific verb+resource: 'CALL THIS AFTER DEPLOYING when there is open feedback. Matches what you just built to open feedback items, resolves them with explanations, and notifies the original stakeholders.' This clearly distinguishes it from siblings like get_feedback (pulling feedback) and triage_feedback (likely categorizing items), establishing a unique purpose.

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 gives explicit context: 'CALL THIS AFTER DEPLOYING when there is open feedback' and outlines a step-by-step flow starting with pulling feedback via get_feedback. It does not explicitly state when-not-to-use or name alternative tools, but the condition 'when there is open feedback' and the flow provide clear usage guidance. A score of 4 reflects the clear context without full exclusion guidance.

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