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

With no annotations, the description carries the burden well: it discloses no key/auth header is forwarded, that the call is free, the privacy constraint on note content, and the possible response statuses including that storage is currently off. It doesn't detail retry/rate-limit behavior, but coverage is strong for a mutation tool.

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?

Front-loads the purpose, then constraints, then the endpoint and privacy caveats. Every sentence adds an operational fact 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?

Despite no output schema, the description explains the return status ('recorded' or 'not_recorded') and its caveat, and covers auth, privacy and usage context. Nothing an agent needs to invoke it correctly 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 100%, so the baseline is 3, but the description adds real meaning by instructing that the answer's decision_id must be included (the schema marks only rating as required) and reinforcing the note privacy constraint.

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 specific verb+resource: submitting a reliability rating ('reliable, unreliable, trustworthy, untrustworthy or confusing') about a ModelSpec answer, and names the exact endpoint it proxies. An agent can distinguish this from siblings like decide or policy_check immediately.

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?

Explicitly scopes when to use it ('After you act on an answer') and when not to ('Not for questions or support'). It also tells the agent to include the answer's decision_id, which is the trigger condition.

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