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

Beyond the annotations, it discloses dedup behavior ('repeated requests share the existing queue entry and increase request_count'), refusal of existing terms and aliases, and the meaning of status. These are non-obvious side effects that an agent could not infer from readOnlyHint=false / idempotentHint=false alone.

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 most important constraint (records a suggestion, not a filter) is front-loaded, and each sentence carries distinct rules. It is somewhat dense with long compound sentences and an awkward clause ('as on freehire's dictionary page'), which costs a point on readability.

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 two-parameter mutation with no output schema, the description covers the outcome (a queued suggestion with a review status), the dedup side effect, and the user-facing message. Nothing an agent needs to call 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 description coverage is 100%, so the baseline is a 3; the description adds meaning by specifying the term should be 'the user's original term' sent 'once per missing term' without a separate prefetch. It does not elaborate further on the kind enum beyond what the schema already documents.

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 states a specific verb and resource ('Request review of a missing specialization, skill or company industry') and immediately disambiguates it from siblings: 'This records a suggestion, not a new working filter or a vacancy.' An agent can tell this apart from search/list/filter tools without opening the schema.

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 ('a specialization, skill or industry the user wanted to filter by but the dictionary cannot resolve') along with an exclusion ('an empty job search alone is not evidence of a missing term'). It also tells the agent what to say to the user, removing guesswork about downstream messaging.

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