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

With no annotations, the description carries the full behavioral disclosure burden, but it only vaguely hints that the output is a 'copy-paste prompt pack with examples'. It does not clarify whether the tool reads code, requires code context, performs an actual check, or what side effects or return behavior to expect.

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 is short but loaded with vague marketing filler such as 'production-ready', 'run today', and 'structured, repeatable workflow'. The useful information is not front-loaded because the core action of the tool is never clearly stated.

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 simple one-parameter tool with no annotations or output schema, the description still fails to explain the central operation: what is being checked, what input is needed, and what the agent should expect back. It is not complete enough to guide correct invocation.

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 single optional 'query' parameter is fully documented in the schema, so the baseline is 3. The description adds no additional meaning about how the query should be scoped or what it affects.

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 largely restates the tool name as a 'codereview check tool system' and then adds marketing language about a 'prompt pack'. It does not explain what the check evaluates, what input it expects, or how it differs from sibling tools like dt-codereview-gen-tool and dt-codereview-tpl-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?

There is no explicit guidance on when to use this tool instead of its siblings, nor when not to use it. The target audience phrase 'for marketing and operations leaders' does not function as a usable selection condition for an agent choosing among many check/gen/tpl tools.

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