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cloudcostwise

cloudcostwise

by cloudwise-app
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

scan

Read-onlyIdempotent

Analyzes an AWS account with local read-only credentials to find wasted resources and estimate monthly savings; optional Cost Explorer checks add small AWS fees.

Instructions

Scan the user's AWS account for waste with their local credentials (read-only; any non-read AWS call is refused). Takes 30-60 s per region; up to 4 regions run at once. COST: the RI/Savings Plans checks call Cost Explorer, billed by AWS at $0.01 per request (a few cents a scan); tell the user before running, and pass include_cost_explorer=false to skip them. regions: comma-separated, or 'all'; default us-east-1 plus the profile's region.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "scan"
  }
}

Input Schema

NameRequiredDescriptionDefault
profileNo
regionsNo
include_cost_explorerNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.18

TDQS

A4.4/5.0
Behavior5/5

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

Goes well beyond the readOnly/idempotent/destructive annotations by disclosing that non-read AWS calls are actively refused, that a scan takes 30-60s per region with up to 4 regions concurrent, and the exact Cost Explorer billing model. The cost warning and user-notification requirement are exactly the kind of context annotations cannot express.

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?

Front-loads the core action, then layers duration, cost, and parameter semantics in short clauses with zero filler. Dense but every sentence adds operational information.

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

Completeness5/5

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

For a zero-required-parameter scan tool with an output schema, the description covers credentials, runtime, concurrency, cost, and region defaults. Return values need not be explained since an output schema exists; only the unexplained 'profile' parameter is a minor omission.

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

Parameters4/5

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

Schema coverage is 0%, so the description must carry the load, and it does for two of three parameters: regions syntax and defaults are spelled out, and include_cost_explorer's effect is explained. The 'profile' parameter is never described, leaving one gap.

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

Purpose4/5

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

States a specific verb and resource: scanning the user's AWS account for waste using local credentials. It is clearly distinguishable from siblings like list_findings and explain_finding, though it never explicitly names them or routes the agent to them.

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

Usage Guidelines4/5

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

Gives concrete pre-run guidance ('tell the user before running') and an explicit opt-out path ('pass include_cost_explorer=false to skip them'), plus defaults for regions. It does not state prerequisites such as needing configured AWS credentials or when to prefer a narrower tool.

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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