leave_review

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds important context about the prerequisite condition (job must be marked complete by human) and that reviews are 'only allowed' under this condition, which suggests permission/validation logic. However, it doesn't describe what happens after submission, error conditions, or whether the action is reversible.

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 consists of two concise sentences that efficiently convey the core purpose and critical usage constraint. Every word serves a clear purpose with no redundancy or unnecessary elaboration, making it easy to parse and understand quickly.

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 mutation tool with no annotations and no output schema, the description does well by specifying the prerequisite condition and scope. However, it could be more complete by mentioning what the tool returns or any side effects. The purpose and usage constraints are clearly communicated, making it mostly adequate for the tool's complexity.

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?

The schema description coverage is 100%, so all parameters are documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema (job_id, rating 1-5, optional comment). This meets the baseline expectation when schema coverage is complete.

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 specific action ('Leave a review') and the target resource ('for a COMPLETED job'), distinguishing it from siblings like 'approve_completion' or 'mark_job_paid' that handle different job lifecycle stages. It uses precise language that immediately conveys the tool's function without ambiguity.

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?

The description explicitly states when to use this tool ('after the human marks the job as complete') and implies when not to use it (for incomplete jobs). While it doesn't name specific alternatives, it provides clear contextual prerequisites that guide proper usage relative to other job-related tools.

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