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

With no annotations, the description fully discloses behavior: stores bytes, enqueues job, costs 10 credits charged immediately, returns specific fields, poll alternative, webhook callback, requires API key, raises if backend missing. This is comprehensive.

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 with a clear main verb, bullet points for key details, and no redundant text. Slightly verbose in listing return fields but acceptable.

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?

Given the tool's complexity (async job, cost, error conditions, output schema), the description covers most aspects: purpose, return value usage, error cases, and alternative. Missing details on parameter constraints but overall adequate.

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 0%, yet the description only adds minimal context: filename is for identification, content_base64 is the bytes, webhook_url for callback. It does not explain format constraints or how each parameter affects behavior, leaving gaps for an AI agent.

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 'Submit a document for asynchronous, high-fidelity conversion (docling)', specifying the action, resource, and asynchronicity. It distinguishes from siblings 'convert_document' (likely synchronous) and 'get_conversion_job' (polling).

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 explains when to use (async conversion), mentions prerequisites (API key, backend config), and how to get results (poll with get_conversion_job or webhook). It does not explicitly contrast with convert_document, but the context is clear enough.

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