Report an OKF bundle's health

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

Annotations already declare readOnlyHint=true and idempotentHint=true, but the description adds substantial behavioral nuance beyond that: it distinguishes between 'stale' (spec-derived) and 'aging' (heuristic), warns against conflating them, and includes error handling for invalid as_of. This provides context that annotations alone cannot convey.

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 well-structured and front-loaded with a clear summary, followed by a necessary disambiguation of stale vs. aging, then Args, Returns, Examples, and Error Handling. Every paragraph serves a purpose; the length is justified by the tool's semantic complexity, and no information is wasted.

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 no output schema, the description fully documents the return JSON structure. It also covers error handling and includes usage examples. Combined with annotations for safety and a straightforward input schema, the description leaves no critical gaps for an AI agent to invoke the tool 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 baseline is 3. The description's Args section restates the schema parameters and adds clarity (e.g., as_of evaluates staleness against a date 'instead of today', response_format default is 'markdown'). While largely redundant with the schema, the narrative context reinforces the semantics, justifying a slightly higher score.

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's function: 'Analyze a bundle for documentation-health problems' and enumerates specific issue types (broken links, missing descriptions, untyped concepts, staleness, unverified/deprecated content, orphans). This is a specific verb+resource that distinguishes it from sibling tools like okf_open_bundle or okf_get_concept.

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 explicit 'Use when' examples ('Is anything in this catalog out of date?', 'What still needs human review?', 'auditing before relying on a bundle') that give clear context for when to invoke the tool. However, it does not mention when not to use it or name alternatives like okf_validate, so it lacks the explicit exclusions that would earn a 5.

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