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

With no annotations, the description carries the full burden and does add real value: it discloses the data provenance (public price pages), recency metadata (fetched_at), the returned statistics (min/median/max, quote percentile), and a mandatory $0.04 USDC x402 payment. It does not state read-only nature explicitly, coverage breadth, or behavior on unknown GPUs, so the disclosure is partial rather than complete.

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?

A single dense sentence that front-loads the core deliverable, then provenance, then return fields, then price. Little waste, though the 'falcon.sol:' prefix costs space without informing tool selection.

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?

Three undocumented parameters, no annotations, and no output schema mean the description should do more. It never explains parameter meaning or accepted values, and gives no coverage or failure behavior, leaving the agent unable to construct a confident request.

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?

All three parameters (gpus, tiers, target_usd_per_gpu_hr) have 0% schema description coverage and none are explained in the description. 'tiers' in particular is ambiguous — GPU classes, cloud commitment tiers, or vendor tiers — and 'target_usd_per_gpu_hr' is only obliquely hinted at by the mention of 'quote percentile'.

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 — listed USD-per-GPU-hour comps pulled from named public price pages (RunPod, Modal, Lambda, CoreWeave) — which distinguishes it from generic comps siblings like get_comps. The leading 'falcon.sol:' identifier is opaque and the verb is implied rather than stated, but the domain is unmistakable.

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 versus get_comps or the other financial siblings, no stated prerequisites or coverage limits, and no indication of what happens when a requested GPU has no listed price. The agent must infer selection logic entirely from the name.

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