Run AI diagnosis

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

The description discloses that the tool calls an AI provider, uses tokens, costs money, and stores the result. This adds behavioral context beyond annotations (readOnlyHint=false, openWorldHint=true, idempotentHint=false) and is fully consistent with them.

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 concise with three sentences, front-loading the primary function, then disclosure of side effects, then prerequisites. No redundant information.

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?

Despite no output schema, the description adequately covers return values (root causes, confidence, fix, source files). It also covers prerequisites and side effects. Lacks only explicit behavior on error handling or large outputs.

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 67%. The description adds no additional meaning beyond what the schema provides for 'annotation_id', 'model', and 'provider'. Baseline of 3 is appropriate.

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 runs an AI diagnosis on an annotation, analyzing DOM, errors, etc., producing root causes, confidence, fix, and source files. It is specific with verb+resource, but does not explicitly differentiate from siblings like 'get_annotation_analysis'.

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: it analyzes annotations for diagnosis and mentions prerequisites (admin enabled AI + diagnosis, key set). It does not explicitly state when not to use or name alternatives, but the context is sufficient.

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