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

No annotations are provided, so the description must fully disclose behavior. It reveals that fix=true requires confirmation, indicating a mutating action, but does not explain what 'diagnoses' does, the role of dry_run, or any side effects of fixing. This is insufficient.

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 a single, front-loaded sentence that communicates the core purpose and the key fix/confirm behavior with no unnecessary words. It is perfectly concise.

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?

With 4 parameters, no annotations, no parameter descriptions, and sibling tools that may overlap, the description is too brief to provide complete context. It doesn't cover the scope of diagnosis, the dry-run option, or when to use fix.

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%, so the description must compensate. It adds meaning for fix (attempts correction) and confirm (required for fix), but dry_run and product_root are left completely unexplained, leaving the agent with incomplete information for safe invocation.

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 tool diagnoses inconsistencies and can attempt to fix them with fix=true. This is a specific verb+resource, but it doesn't differentiate from sibling tools or specify the type of inconsistencies.

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?

No explicit guidance is provided on when to use this tool versus alternatives. The description implies it is for diagnosing inconsistencies, but there are no exclusions, prerequisites, or alternative references.

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