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

Beyond the readOnlyHint/openWorldHint annotations, the description discloses the essential operational facts: the model and vector size, the 100-text batch ceiling, the exact price ($0.002 USDC), the payment rail (x402 on Base, Solana or Arc), and that failed calls are not billed. That payment/auth context is exactly what an agent needs before invoking a paid endpoint.

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?

Two dense sentences with zero filler: capability and limits first, then use cases, then cost. The most decision-relevant facts (model, dimensions, batch cap, price) are front-loaded.

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 an output schema present, return values need not be explained, and the description still covers capability, model, dimensionality, batch limit, intended uses, and cost/payment mechanics. Nothing an agent needs to call this 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 single `text` parameter is already documented as a string or array of up to 100 strings, so the description's batch-limit mention restates rather than adds. The 'multilingual' framing adds slight semantic value but not parameter-level detail. 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 description states a specific operation on a specific resource: multilingual text embeddings from BGE-M3 at 1024 dimensions, batched up to 100 texts. It is clearly distinguishable from adjacent text tools like rerank or text_chunk, though it never names a sibling explicitly.

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?

It lists intended downstream uses (search, RAG, clustering), which implies when to call it, but gives no explicit when-not guidance or comparison to alternatives such as rerank or classify, which an agent choosing among many text tools would benefit from.

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