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

Annotations already mark this as read-only, idempotent, and non-destructive, so the addition of behavioral context is valuable. The description discloses the monthly publication cadence, the live source (chinamoney.com.cn), the rolling ~1-year data limitation, and the cap at 12 announcements — all beyond what annotations provide.

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 longer than average, but nearly every sentence earns its place by explaining what the rates are, how they are published, what data is returned, and what limitations exist. It is front-loaded with the core purpose and uses the rest for necessary context; a slight trim could improve conciseness without losing value.

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?

Even without an output schema, the description tells an agent exactly what to expect: monthly rows with 1-year and 5-year rates plus announcement dates, a `latest` field, a maximum of 12 rows, and live keyless access. Combined with the fully documented `months` parameter, the agent has enough to call the tool correctly and interpret the result.

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 input schema already describes `months` fully (1-12, default 12, capped at 12), so the baseline is 3. The description adds meaningful behavioral context by explaining that the endpoint only exposes a rolling ~1-year window, which justifies the cap and helps an agent reason about why large values are not honored.

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 opens with a specific verb and resource: "China's PBOC Loan Prime Rate history — the 1-year and 5-year benchmark lending rates, each with its official reference/announcement date." It clearly distinguishes this tool from the sibling china_lpr_latest by emphasizing the historical series and the 12-month window, while still acknowledging a `latest` field.

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 lists concrete user intents such as "what is the current PBOC LPR" and "when did the PBOC last cut the LPR". However, it never explicitly says when to prefer this tool over the sibling china_lpr_latest, nor does it state any exclusions or alternatives, leaving that routing implicit.

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