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

The annotations already declare readOnlyHint=true and openWorldHint=false. The description adds useful behavioral context beyond that: 'A forecast, not a promise' signals uncertainty, and it lists the result contents (probability, confidence, last confirmed reset time, active official signal).

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 short sentences with no filler. The core value is front-loaded, and the 'forecast, not a promise' disclaimer is concise rather than repetitive.

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 tool with one optional parametereb and no output schema, the description covers the key output components and the uncertainty framing. It could be more explicit about the probability format or range, but an agent can invoke the tool correctly without needing more.

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 only parameter, locale, is fully documented in the schema with an enum and a default value. The description adds nothing about locale semantics, but with 100% schema description coverage, the baseline score of 3 is appropriate.

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 identifies the resource (OpenAI Codex usage-limit reset) and the specific kind of answer (probability forecast over 24 and 48 hours). It is specific enough to be told apart from generic status tools, though it does not explicitly contrast with the sibling tools by name.

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?

There is no guidance on when to use this tool instead of get_codex_status or get_reset_timeline, and no exclusions or alternative conditions are stated. The time-bound forecast wording implies a use case, but the routing decision is left entirely to the agent.

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