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

Beyond the annotations (which already cover readOnly/non-destructive), the description discloses the exact metric being summed, the crucial semantic caveat that missing days are unknown rather than zero, and the cost model of one data unit per page. Those are behavioral facts an agent could not derive from the structured fields and that materially affect result interpretation and call budgeting.

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?

Front-loaded with the core behavior, then caveats, then cost/pagination. Every sentence carries distinct information; the metric definition, the 'not zero' warning, and the data-unit cost are all non-redundant.

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?

There is no output schema, so the description must explain what comes back, and it does precisely (per-day, per-provider, per-node-size available vs known configuration-hours). Combined with annotations and a fully documented schema, an agent has everything needed to call this correctly and interpret the response.

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%, so gpu, provider, and the pagination object are already fully documented. The description only restates that provider is an optional narrowing filter and repeats the page defaults, adding no new syntax or constraint information. Baseline 3 applies when the schema does the heavy lifting.

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?

States a specific verb and resource (day-by-day stock) with explicit scope: one GPU model, last seven days, per provider and node size, measured as available vs known configuration-hours. That metric definition is distinctive enough to separate it from get_price_history and get_market_snapshot without opening their schemas.

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?

Scope is clear enough to imply when the tool applies (historical availability, not pricing or uptime), and the 'observed availability, not uptime or launch guarantees' line sets a boundary on interpretation. However, it never explicitly names a sibling or says when to prefer this over get_market_snapshot or get_prices, so routing is left to inference.

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