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alialbaker

cloudprice-mcp

compare_clouds

Find the cheapest equivalent VM across AWS, Azure, and GCP by specifying vCPUs and memory. Compare costs and savings between clouds.

Instructions

Find the cheapest equivalent VM across AWS, Azure, and GCP for a single target spec (vCPUs and memory). Returns the best-fit SKU per cloud sorted by monthly cost, plus the absolute and percent savings of the cheapest vs the most expensive option.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vcpusYes
memory_gbYes
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses that results are sorted by monthly cost and includes savings calculations. However, it does not mention potential side effects (none expected), data sources (e.g., on-demand vs reserved pricing), rate limits, or caching. Adequate but lacks depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no repetition, front-loaded with the core purpose. Every sentence adds value: first sentence states purpose and input, second describes output. Extremely efficient for the information conveyed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity (two parameters, no output schema), the description covers the essential: input spec, output format (per-cloud SKU sorted by cost, plus savings). It lacks explicit return type details, but savings description ('absolute and percent savings of the cheapest vs the most expensive') is sufficient. Near-complete for this scope.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%. The description restates the parameter names ('vCPUs and memory') but adds no additional meaning beyond the field names (e.g., units, accepted ranges, or what constitutes a valid spec). It does not clarify that vcpus is integer count or memory_gb in gigabytes. Minimal added value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description explicitly states 'Find the cheapest equivalent VM across AWS, Azure, and GCP for a single target spec (vCPUs and memory).' It clearly identifies the action (find), the resource (cheapest equivalent VM), and the scope (cross-cloud, single spec). This distinguishes it from siblings like the individual cloud price getters or broader compare_compute_inventory.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for a single target spec via 'for a single target spec,' but does not provide explicit when-to-use or when-not-to-use guidance. It does not mention alternatives (e.g., compare_compute_inventory for multiple specs, or single-cloud tools for specific cloud prices). Minimal guidance beyond the implied scope.

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

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