compare_spot

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

No annotations are supplied, so the description carries the full burden, and it does disclose the return contents (per-cloud best-matching SKU, on-demand cost, spot cost, savings, eviction characteristics) and the ranking order. It also flags that each cloud uses different pricing and eviction models, which is real behavioral context. Gaps remain: no statement on price freshness/caching, savings units (percent vs absolute), or behavior when no matching SKU exists.

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 first two sentences are front-loaded and information-dense with the return contract. The final sentence, however, is largely promotional ('The only multi-cloud spot comparison anyone publishes openly') and pads the definition, even though its point about differing pricing/eviction models is worth keeping in a tighter form.

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?

With no annotations and no output schema, the description must cover both safety/behavior and return values, and it covers the return shape and ranking well. It stops short of covering failure modes, freshness of pricing, or any cost/rate-limit caveats, which leaves a modest gap for a tool whose output is used for decisions.

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 only 33% – only 'targets' is documented in the schema. The description clarifies that vcpus and memory_gb jointly define the shape being priced, which adds some meaning, but it says nothing about how best-match tolerance works, what memory rounding implies, or what omitting targets does beyond the schema's own default note.

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 ('Compare spot / preemptible pricing') plus the exact input shape (vCPU + memory) and the four clouds covered. The 'spot/preemptible' framing plus the named return fields make it clearly distinct from on-demand siblings like compare_clouds and from compare_gpu_workload.

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 use case is implied by the scope (comparing spot pricing for a given shape), but there is no explicit when-to-use or when-not guidance and no sibling is named as an alternative. An agent must infer that compare_clouds is the on-demand counterpart and compare_workload is the sizing/other counterpart.

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