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

With no annotations, the description carries the transparency burden. It usefully discloses that valuations are 'AI-synthesized', the per-endpoint pricing, and the on-chain GoPlus NFT context. However, it does not state whether the tool is read-only, what output shape to expect, rate limits, data freshness, or potential variability in results.

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: it starts with the tool's purpose, then a coverage line, then a clear bulleted endpoint list. It is reasonably sized for an API with 11 endpoints, though the truncated sentence 'Real-' and the repeated pricing labels add slight noise. Overall, it is front-loaded and organized well.

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?

For a tool with 10 parameters, 11 endpoints, and no output schema or annotations, the endpoint list provides a useful overview and helps an agent pick an action. However, it lacks per-endpoint required parameter information, return format descriptions, language/chain constraints, and operational notes, so an agent may need trial and error to invoke it correctly in some cases.

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%, so the baseline is 3. The endpoint list adds meaningful semantics to the 'action' parameter by describing each endpoint's purpose. However, some parameter descriptions in the schema are tautological (e.g., 'lang', 'item1', 'item2'), and the tool description does not clarify which parameters are needed for which endpoints or provide additional parameter-specific details.

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 identifies the tool as 'Global collectibles market intelligence API' with 'AI-synthesized valuations' for a specific domain, and lists 11 distinct endpoints with concrete actions (value, grade, authenticate, etc.). This strongly differentiates it from sibling tools, which are named as other domain-specific pulse tools.

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 endpoint list gives clear context about what the tool can do and implies when to use it (collectibles valuation/investigation), but it does not explicitly state when to use this tool over alternatives or when not to use it. There is no guidance on which endpoint to choose beyond the brief one-line descriptions, nor any exclusions.

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