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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false; the description adds the crucial human-in-the-loop detail that nothing is transmitted and the user must review and open the link. That is real value beyond the structured fields, though it does not describe the URL's lifespan or any validation/precondition on inputs.

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?

Three short sentences: what it returns, when to use it, then the key safety caveat. The deliverable and the no-side-effect guarantee are both front-loaded, with no filler.

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?

There is no output schema, and the description compensates by naming exactly what comes back (contact form URL and mailto link). For a three-parameter, read-only helper with full schema coverage, nothing an agent needs before calling is missing.

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 already 100%, so the baseline is 3. The description earns a notch more by mapping its scenarios (AI project, company data, feedback) onto the opaque German enum values ki_projekt / firmendaten / sonstiges, which the schema only labels generically as 'Topic category'.

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 concrete verb and deliverable: returns a prefilled contact-form URL plus a mailto link for contacting Overfit. It also scopes the cases (custom AI project, company data packages, feedback), which separates it from siblings like register_feature_interest or post_to_agent_board.

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?

It clearly signals when to use it — whenever the user wants to contact Overfit — and gives three example scenarios. It stops short of naming alternatives (e.g. register_feature_interest for feature votes) or stating when not to use it, so it is context-rich but not fully routing.

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