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

Annotations already declare readOnly, idempotent, non-destructive, open-world, so the safety profile is covered. The description adds real behavioral context beyond them: data source (TAIFEX OAS), that it is not live, that it covers both regular and after-hours sessions, and crucially that an ambiguous name returns candidates rather than erroring or guessing — a non-obvious control-flow behavior an agent must handle.

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 core purpose first, then input forms, then scope exclusions. The one structural weakness is that the entire content is duplicated bilingually (Chinese mirror of the English), roughly doubling length without adding information for a single-language reader.

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?

An output schema exists so return-value explanation is not required, yet the description still sketches the payload. For a single-parameter, read-only, disambiguation-prone snapshot tool, the description covers source, freshness, scope boundaries, ambiguity handling and alternatives to siblings — essentially complete, with only minor redundancy in the bilingual restatement.

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 100% and there is only one parameter, so the baseline is 3. The description goes beyond the schema by listing concrete accepted codes ('TX', 'MTX', 'TMF', 'CDF') and Chinese names ('台指期', '小台', '台積電期貨') and by defining the multi-match resolution behavior, which the schema does not express.

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?

Names a specific verb/resource combination — one TAIFEX futures contract for the latest trading day — and enumerates the returned data (OHLC, change, volume, settlement, open interest by month, near-month summary, institutional/large-trader positions, final settlement). It explicitly excludes options and aggregate futures chips, routing those to dataset.search or snapshot.market, so it is distinguishable from siblings without opening any schema.

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?

Clearly states the input forms accepted ('TX', 'MTX' codes or Chinese names) and the disambiguation workflow: an ambiguous name returns candidates only, and the agent should confirm with the user then re-query by code. It also points to dataset.search / snapshot.market for options and overall futures positioning. It lacks an explicit statement of when this tool is preferred over the closer sibling snapshot.market beyond the scope hint, but the routing guidance is solid.

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