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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds real behavioral context beyond that — a scope restriction and a privacy constraint ('Do not include personal information about the user') — but says nothing about what happens to the feedback afterward, whether a submission is confirmed, or any rate limiting. There is mild tension between the verb 'send' and readOnlyHint=true, though submitting feedback to a feedback channel does not modify the monologue corpus, so it is not a contradiction.

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 sentences, front-loaded with the core action, then the scope bound, then the privacy constraint. No filler, no restatement of the tool name, and each sentence adds a distinct constraint.

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?

With 100% schema coverage, no output schema, and a flat 10-parameter object, the description does not need to explain parameters or return values. It covers the two things the schema cannot — scope and privacy — leaving only minor unstated items such as post-submission confirmation or rate limits.

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 ten parameters — including the nuanced conversation_id reuse rule and the 'pass "unknown" rather than guess' instruction for llm_model — are already fully documented. The description only restates the feedback_type categories in prose and adds no syntax or format detail the schema lacks. Baseline 3 applies when structured data carries the whole burden.

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 and resource ('Send feedback about this Shakespeare monologues server') and immediately enumerates the acceptable subject matter: a missing monologue/play/capability, a problem with a result, or praise. Combined with the sibling list of purely read-only retrieval tools, an agent can tell instantly that this is the sole outbound/write-channel tool.

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 bounds usage: 'Only for feedback about these tools, not about other tasks' gives a clear when-not, and the feedback_type schema enumerates when to pick missing_capability vs issue vs praise vs other. This is about as close to explicit when/when-not/alternative routing as a feedback tool can get.

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