预采集债券与期权数据

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

With no annotations, the description carries the full burden of behavioral disclosure. It does convey the core behavior — a one-time bulk fetch writing to local cache to avoid repeated network calls — which appropriately signals a stateful write operation. However, it does not disclose cache refresh semantics, idempotency, operation duration for large history pulls, or how an agent can verify or clear the populated cache afterward.

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 sentences with no wasted words. The primary purpose is front-loaded in the first sentence, and the companion-tool relationship is given in the second. Every sentence earns its place.

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 zero-parameter prefetch tool with an existing output schema, this description is nearly complete: it names the data scope, the caching behavior, and the companion tool. The only gap is guidance on post-call verification (e.g., using cycle_cache_status or cache_status to confirm the cache was populated) and any note about the expected time cost of a full-history pull.

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?

The tool has zero parameters and an empty input schema, so the baseline of 4 applies — there is nothing for the description to document about arguments. The description appropriately focuses on what data is collected (bond yield curve, QVIX full history) instead of inventing parameter 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 states a specific action (一次性拉取/prefetch to cache), a specific resource (债券收益率曲线 and QVIX全量历史数据), and a destination (本地缓存). It also distinguishes itself from query siblings like bond_yields and option_ivix by clearly framing this as a collection/caching operation rather than a query.

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 description gives clear usage context: call this to avoid repeated network requests when data will be queried multiple times. It names the companion tool cycle_collect, but does not explicitly exclude alternatives such as bond_yields, option_ivix, or cycle_cache_status, nor does it state when NOT to use this tool.

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