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

Annotations only flag this as a non-read-only, non-idempotent write; the description adds substantial context beyond them: free on every plan, no account needed, does not consume the monthly allowance, rate limits (10/hour per account, 5 without), the return shape, and a privacy caveat ('Do not include personal data beyond what the user asks you to pass on'). This is rich operational detail an agent cannot get from structured fields.

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-loaded with purpose, then usage, then examples, then limits/return. Every sentence carries load, but the two full JSON examples and the inline rate-limit sentence make it longer than strictly necessary; a tighter phrasing would preserve the same routing value.

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, yet the description states the return value ('{feedback: {id, kind, status, created_at}, note}'), covers the write semantics, rate limits, and account requirements. Nothing an agent needs to invoke this 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 goes beyond it by demonstrating how refs fields pair with each kind (indicator/place/period/url for a data_error; place/source for a data_request) through two worked examples. This adds practical mapping guidance the schema enumerations alone do not convey, though it stops short of full per-parameter explanation.

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 opening sentence states a specific verb and resource ('Send a message to the Invokely team') and the rest enumerates the exact scenarios (missing statistic, wrong value, suggestion, bug) that distinguish this tool from all read/lookup siblings. An agent can tell instantly this is the feedback channel, not a data-retrieval 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?

Explicit when-to-use is given per kind: 'call it when the user asks for a statistic... Invokely does not have,' 'when a value looks wrong,' 'wants to suggest something,' 'reports a problem with Invokely itself.' The description also instructs the follow-up action ('then tell the user it was sent'), leaving nothing to inference.

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