Limit breakdown

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It does add useful interpretive context, like cache reads weighing 1/70 of fresh input and the distinction between saving money and saving limit, which informs how to interpret results. But it does not explicitly state read-only behavior, side effects, or how the computation is performed, leaving gaps for a no-annotation tool.

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 a compact four-sentence paragraph with no filler. It front-loads the core purpose, then provides contextual insight, and finally maps each view option. The sentence about cache weights and money-vs-limit earns its place by explaining a nuance that affects interpretation, though it could arguably be more concise 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?

For a tool with a single optional parameter and no output schema, the description is largely complete: it states what the tool does, the available views, and even offers conceptual background on rate limit behavior. It does not describe the output shape, which an agent might need to parse, but the simplicity of the tool keeps this a minor gap rather than a crippling one.

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?

Schema coverage is 100% because the parameter 'view' has an enum and a description, so the baseline is 3. The description adds significant meaning by defining each view value: windows (burn per window), fit (per-model weights and multipliers), steps (every change point), weekly (7-day windows). This goes well beyond the schema's generic 'Which angle to report' and helps an agent select the correct value.

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+resource: 'Works out what drives the 5-hour and weekly rate limits.' It then enumerates the four view modes, making the tool's purpose unmistakable and clearly distinct from siblings like current_limits or subscription_value, which sound like they report current values rather than explain their drivers.

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 when the tool is useful—when trying to understand what drives rate limits rather than just the limits themselves—and provides helpful domain context ('On a subscription the real constraint is the limit gauge, not dollars'). However, it never explicitly contrasts this tool with sibling tools or states when not to use it, so guidance remains implied rather than explicit.

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