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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), yet the description still adds substantial behavioral context beyond them: days without a snapshot are returned as gaps rather than interpolated, typical latency under 0.1 s, a USD 0.002 per-call cost, a free tier of 10 calls per IP per UTC day, and a docs link. These are exactly the operational facts an agent needs before invoking a metered 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?

Front-loaded with the tool's identity and return shape, then progressively adds caveats and cost. The opening 'utilpeek: GPU price index:' restates the name and title before the substantive sentence, which is mild redundancy rather than bloat. Every other sentence carries distinct information.

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?

An output schema exists, so return structure need not be explained, yet the description still covers the semantics that matter: what the prices represent, the missing-day/no-interpolation rule, latency, cost, and quota. Nothing an agent needs to call this correctly and interpret the result is absent.

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 description coverage is 100%, so the schema already documents chip, from, and to including formats and defaults. The description contributes one piece of extra meaning not in the schema ('per GPU-hour' as the unit of the returned prices), but otherwise defers to the schema. 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 ('Returns a GPU chip's daily rental price history') and enumerates the exact series returned: lowest/median on-demand list price, lowest spot, Akash median bid, and free GPUs. The 'daily ... over time' framing cleanly separates it from the sibling get_gpu_prices, which reads as a current-snapshot tool. An agent can select between them without opening either schema.

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?

Usage is only implied by the word 'history' and 'over time' – the description never states when to prefer this over the sibling get_gpu_prices, nor any exclusion. It does clarify that the data reflects list prices and marketplace bids rather than executed trades, which is useful scoping, but that is about data meaning rather than when-to-call guidance.

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