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

No annotations are provided, so the description carries the full burden, and it does disclose the key behavioral distinction: accepting mutates category rules and updates scan scores, while rejecting only logs. It omits other traits such as permission requirements, reversibility of an accept, and idempotency, which is why it is not a 5.

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 the accept-vs-reject behavioral delta, then the argument list – a sensible ordering that lets an agent stop reading early. The Args block is necessarily long given nine undocumented parameters, but it is formatted cleanly rather than padded.

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?

An output schema exists, so return values need not be detailed. Given a 9-parameter, 6-required mutation tool with no annotations and no schema descriptions, the description supplies the missing parameter meaning, the mode-dependent side effects, and the upstream workflow link, which is everything needed to call it correctly.

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 0% – the schema gives only bare titles – so the description must compensate and it does, documenting all 9 parameters. It adds real meaning beyond names: categories keys with an example, severity's enumerated levels, the 'Before'/'After' provenance for before_code/after_code, and the tie-back of scan_uuid/project_name to suggest_code.

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 pair (accept/reject) plus the resource (code recommendation) and anchors it to a concrete upstream source: 'a previous suggest_code scan'. An agent can distinguish this from siblings like suggest_code or score_pull_request without opening any 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?

Clearly establishes the usage context (only meaningful after a suggest_code scan) and explains the two modes, with the side-effect difference between them spelled out. It does not state exclusions (e.g. what to do if scan_uuid is unknown or the recommendation is stale), so it stops short of a full when/when-not treatment.

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