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chaandannn

nable (finops-mcp)

scan_waste_patterns

Scan your AWS account for cloud cost waste patterns across compute, storage, database, network, AI, and governance, providing confidence scores, monthly waste estimates, and remediation steps.

Instructions

Scan for cloud cost waste patterns using nable's proprietary pattern library.

Runs 13 waste fingerprints across compute, storage, database, network, AI, and governance categories. Each finding includes confidence score, monthly waste estimate, and specific remediation steps.

Args: account_id: AWS account ID to scan min_monthly_waste: only return findings above this monthly USD threshold categories: comma-separated filter e.g. "compute,storage" (omit for all)

Returns structured findings sorted by monthly waste descending, with total_monthly_waste and total_annual_waste summary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
account_idYes
categoriesNo
min_monthly_wasteNo
Behavior2/5

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

No annotations are provided, so the description must handle behavioral disclosure. While it describes the scan's output and categories, it does not explicitly state that the tool is read-only, required permissions, or potential side effects. For a scan tool, this lack of safety disclosure is a significant gap.

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

Conciseness4/5

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

The description is well-structured with a clear purpose sentence, a details paragraph, and a labeled Args section. It is reasonably concise, though the Args block could be integrated more efficiently. Every sentence adds value.

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 lack of output schema, the description adequately explains the return format (structured findings sorted by waste, with totals). It covers the key aspects of the tool's operation, but missing details on error handling or what happens with invalid inputs.

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

Parameters5/5

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

The tool description fully explains all three parameters in a separate Args section, adding meaning beyond the bare schema. It describes account_id as 'AWS account ID', min_monthly_waste as a USD threshold, and categories as a comma-separated filter with an example. This compensates completely for the 0% schema description coverage.

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?

The description clearly states the tool's purpose: scanning for cloud cost waste patterns using nable's proprietary pattern library. It specifies that it runs 13 waste fingerprints across multiple categories, which distinguishes it from other audit and scan tools in the sibling list.

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

Usage Guidelines2/5

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

The description does not provide guidance on when to use this tool versus alternatives. It mentions 'AWS account ID' indicating AWS-specific usage, but does not explicitly tell the agent when to prefer this tool over similar ones like audit_aws_waste or scan_cloudwatch_waste.

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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