usage_status

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

With no annotations provided, the description carries full burden. It discloses auth behavior (reads OAuth token), logging behavior (auto-logs to history), and data source (same endpoint as IDE bar), but does not mention read-only nature, rate limits, or potential side effects beyond logging.

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 very concise at two sentences, each adding essential information: purpose with specific data types, and technical details (auth source, logging). No redundant or vague phrases.

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 output schema and low complexity, the description adequately explains return values (session, weekly usage, reset times, extra credits) and covers auth and logging. It lacks mention of error conditions or prerequisites beyond the token file, but is otherwise complete for a simple read 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?

The tool has zero parameters and 100% schema description coverage, so baseline is 4. The description adds context by detailing the returned data types and auth mechanism, going beyond the bare schema.

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 the tool fetches real-time Claude.ai subscription usage, specifies the data types (5h session, 7d weekly utilization, reset times, extra credits), and distinguishes itself from sibling tools like usage_delta and usage_forecast by referencing the same endpoint as Claude Code's IDE bar.

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 mentions reading OAuth token and auto-logging to history, providing some context on setup and side effects, but does not explicitly compare with sibling tools or state when to use vs alternatives.

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