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

Annotations already declare readOnly, openWorld and non-idempotent, and the description adds real context beyond them: $0.01 per call via x402 USDC or a card key, failed calls free, and an explicit warning that repeats are not free. It also documents accepted formats and the 3 MB cap, which is exactly the kind of operational detail an agent needs before spending money.

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?

Front-loaded with capability, then a compact run of facts about formats, use cases, pricing and safety — every sentence carries information. It is dense but reads as a single deliberate block rather than filler.

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 still explains what comes back: a detailed description including visible text, or an answer to the question. Combined with format limits, price, failure policy and the read-only guarantee, nothing needed to invoke it correctly is missing.

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%, and the schema already documents the URL format, size cap, 300-character question limit and the default behavior. The description adds only the framing that the default is a detailed description including visible text; useful but not meaningfully beyond the schema, so baseline 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 first sentence states a specific verb and resource — a vision model answering about an image at a public URL — and spells out the two modes (detailed description vs. a targeted question). This clearly separates it from the text-only ai_* siblings and from the opaque 'image' tool.

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?

Concrete use cases are enumerated (alt text, OCR-style screenshot reading, chart reading, content checks), which gives the agent solid selection signal. It does not explicitly say when to choose a sibling instead, e.g. transcribe or ai_answer, so it falls just short of a 5.

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