get_quota_summary

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

No annotations are provided, so the description carries the burden. It discloses that providers without a configured token report a config error instead of failing the whole call, which is useful behavioral context. However, it does not describe the return structure or other edge cases.

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 concise sentences. The first sentence immediately states the purpose, and the second adds a key behavioral detail. No wasted words.

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 the lack of parameters and output schema, the description adequately covers the tool's behavior. The error handling detail is valuable. It could elaborate on the return format, but overall it is sufficient for an agent to understand and invoke the tool.

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 the description naturally cannot add parameter details. Per the rules, baseline 4 applies, and the description adds no unnecessary confusion.

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 it returns a unified quota summary across all configured providers, listing examples (Claude Code Max, Kimi, Z.ai). This differentiates it from siblings like get_provider_quota, which targets a single provider.

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 implies use when an aggregated view across providers is needed, but does not explicitly state when not to use it or compare with alternatives like check_quota_health or get_provider_quota.

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