validate_knowledge

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

With no annotations, the description carries the full burden. It discloses that files are flagged as MISSING, and that fix=true will automatically remove stale entries, with a caution. It doesn't mention all edge cases (e.g., reversibility, dry-run), but the key destructive behavior is clearly stated.

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 four sentences long, with the main purpose upfront, followed by concrete behavioral details, usage cadence, and parameter guidance. No wasted words or redundancy.

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 moderate-complexity tool with no output schema and no annotations, the description covers purpose, behavior, usage, and both parameters. It could be slightly more detailed about return values, but the core information is complete enough for an agent to use 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 coverage is 100%, so the schema already fully describes both parameters. The description restates the parameter usage (featureName and fix) but doesn't add significant new meaning beyond what the schema provides.

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 verb 'check' and the resource 'registered file paths across projects, features, and type mappings', with the specific outcome of detecting stale entries. This distinguishes it from narrower sibling tools like check_type_mapping by emphasizing the broad scope.

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 provides clear context for when to use the tool ('periodically to keep the knowledge graph in sync') and how to narrow scope with featureName. It doesn't explicitly mention alternatives or when not to use it, but the usage context is sufficient.

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