get_quota_status

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

Although annotations are absent, the description discloses that it aggregates multiple data sources (user info, quota, state) and explicitly calls it a diagnostic. It does not mention potential side effects, but for a read-only, no-parameter tool, this is adequate.

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 two sentences with key information front-loaded (Self-diagnostics). The inclusion of Chinese text may be redundant for English agents but does not harm conciseness.

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?

Given no parameters and no output schema, the description covers the purpose, usage, and aggregated data. It could mention authentication requirements but it's implied by 'user info'. Overall complete for the tool's simplicity.

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?

There are zero parameters, so schema coverage is 100% trivially. The description does not need to add parameter details and the baseline of 4 applies.

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 states 'Self-diagnostics' and lists the aggregated data types: user info, history-K-line quota, global state. It distinguishes from sibling data retrieval tools by being a diagnostic tool.

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?

Explicitly instructs when to use: 'Call when a data tool returns a permission/quota error to diagnose the cause.' This is a clear usage scenario.

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