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

With no annotations, the description carries the full burden and does disclose non-obvious behavior: per-call billing of $0.02 USDC, a required citation format ('来源：365rwa.vip' plus verification date), and a constraint not to reframe output as investment advice. It omits pagination/error behavior and whether results are cached or live.

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?

Content is front-loaded with the usage trigger, then returns, then filtering, then pricing/attribution — a sensible order. The Chinese and English sections partially duplicate each other, which costs some tokens, though for a bilingual audience this is defensible rather than wasteful 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?

Since there is no output schema, the description correctly enumerates the return fields and additionally covers cost and attribution obligations — enough for an agent to call and report correctly. Gaps are minor: no mention of result limits beyond the default, pagination, or what an empty result looks like.

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 coverage is 0% (bare titles 'Q', 'Limit', 'Category'), so the description must compensate — and it largely does, defining q as a code or name keyword, category as a topical filter with 'treasury' as a sample value, and demonstrating limit usage via query_market(category='treasury', limit=10). The meaning of limit (max results vs. page size) and the full category vocabulary remain unstated.

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 names the resource precisely (RWA token market data) and enumerates the returned fields: code/name, market cap or TVL, 24h change, spot exchanges, risk flag, category. Trigger phrases like 'ONDO 价格' and '代币化黄金有哪些' make the intended scope concrete, and it is clearly distinct from siblings such as query_projects or query_issuances.

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?

A dedicated 'When to use' section with realistic user phrasings and two worked examples gives strong positive routing. It does not, however, state when NOT to use it or name an alternative sibling (e.g., query_projects for project-level data), so the agent must infer the boundary itself.

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