validate_timeline

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

No annotations are provided, so the description bears full burden. It does not disclose whether the tool is read-only, destructive, or what side effects exist. The term 'health check' suggests non-modification but is not explicit, and return values are unmentioned.

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 covering the purpose and scope. It could be slightly improved by front-loading the verb and resource, but is efficient.

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 validation tool, the description omits crucial details about output format (e.g., list of issues, structure). Without this, an AI agent cannot properly interpret results, especially given no output schema.

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% with descriptions for both parameters. The description adds minimal extra meaning by listing check categories, though 'issues' does not match the enum 'offsets' exactly. Overall, the schema already covers parameter details.

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 'comprehensive timeline health check' and lists specific issues (flash frames, gaps, duplicates), distinguishing it from sibling tools like detect_flash_frames and detect_gaps which are single-purpose.

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 usage for an overall health check but does not explicitly state when to use this tool versus running individual detection tools, or any prerequisites or exclusions.

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