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

No annotations are provided, so the description carries the full transparency burden. While it lists what is checked, it does not disclose the output format, any limitations (e.g., heuristic nature), or whether the tool is read-only. The agent is left without key behavioral context.

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 concise sentence that gets straight to the point. It is front-loaded with the verb 'Check' and immediately enumerates the types of placeholders scanned. No wasted words.

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?

The tool is simple with only 2 parameters, both documented in the schema. However, there is no output schema, and the description doesn't explain what the tool returns, leaving a gap in completeness. The description clearly states the purpose but not the result format.

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 100%, with both parameters (code and filename) already described in the schema. The description adds no additional meaning beyond the schema, so the baseline score of 3 applies.

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 checks for placeholder code, dummy data, TODO/FIXME comments, and incomplete implementations. This is a specific verb and resource set, making the purpose clear, though it does not explicitly differentiate from sibling tools like analyze_code or validate_code.

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 implies when to use the tool (when you want to check for placeholders), but it provides no explicit guidance on when not to use it or how it compares to alternatives. No exclusions or alternative tools are mentioned.

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