submit_feedback

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

With no annotations provided, the description carries full burden. It effectively discloses key behavioral traits: it generates a URL (not submitting data directly), requires user action ('user clicks the link'), and is for reporting specific issues ('calculation errors or data issues'). It doesn't mention rate limits, authentication needs, or error handling, but covers the core behavior adequately.

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 perfectly concise with two sentences that each earn their place. The first sentence states the purpose and mechanism, the second provides usage guidance. No wasted words, and the most important information (what it does) is front-loaded.

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 tool with no annotations and no output schema, the description provides good contextual completeness. It explains what the tool does, when to use it, and the user interaction required. The main gap is lack of information about the return value (what the generated URL looks like), but otherwise it's quite complete for its purpose.

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 description coverage is 100%, so all parameters are documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain how parameters map to the GitHub Issue template). Baseline 3 is appropriate when the schema does the heavy lifting.

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 the specific action ('Generate a pre-filled GitHub Issue URL') and resource ('for reporting calculation errors or data issues'), distinguishing it from all sibling tools which are tax calculation/analysis tools rather than feedback submission tools. It explicitly notes 'No data is sent — the user clicks the link to submit', which further clarifies the 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 explicit guidance on when to use this tool: 'Use this after verifying the user's inputs.' This creates a clear usage context (post-verification) and implicitly distinguishes it from tools that perform calculations or analysis (the sibling tools).

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