tokonomix_relay_human_feedback

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

With no annotations provided, the description carries the full burden. It discloses privacy handling ('stored admin-only, never returned verbatim'), the difference in reward rate versus agent-source rate, and the fallback behavior when disabled ('returns a clear "not enabled" message instead of an error'). It also explains where request_id comes from, adding meaningful behavioral context.

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 long but efficiently packed; every sentence earns its place. It is front-loaded with the core purpose, then proceeds through usage constraints, parameter sources, legend, privacy, reward, and error behavior. Dense but structured, with separators that aid scanning.

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 three-parameter tool with no output schema, the description is remarkably complete. It covers when to use (human feedback relay), how to get request_id, what each choice means, optional free_text constraints, privacy, reward implications, and disabled-platform handling. No important aspect appears 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 100%, so baseline is 3. The description adds value beyond the schema: it tells the caller exactly how to obtain request_id (from the billing breakdown line and x_council.request_id metadata), explains the choice legend in a human-mapping context, and provides extra detail about free_text trimming and privacy. This exceeds 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 clearly states the tool's action: 'Relay the HUMAN end-user's verdict on a consensus call.' It explicitly distinguishes itself from sibling tokonomix_rate_consensus (the AGENT's own rating), and the verb 'Relay' with the resource 'human end-user's verdict' is specific and unambiguous.

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?

Usage conditions are explicit: 'Use this ONLY when a real human in the session actually told you what they thought' and 'NEVER fabricate or guess... if no human weighed in, do not call this tool.' It also contrasts with tokonomix_rate_consensus to clarify when each applies, providing clear decision guidance.

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