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nable (finops-mcp)

by getnable

Scan waste patterns

scan_waste_patterns
Read-only

Scan AWS accounts for cloud cost waste patterns across compute, storage, database, network, AI, and governance. Returns findings with 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. Auto-discovered from the connected AWS account when omitted. 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. Examples: - "Scan for waste patterns" - "Any recurring waste in this account?"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
account_idNo
categoriesNo
min_monthly_wasteNo
Behavior4/5

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

Beyond annotations (readOnlyHint=true), the description reveals that it runs 13 specific fingerprints, auto-discovers account_id, and returns findings sorted by waste with summaries. Does not disclose any destructive side effects, which aligns with annotations.

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?

Well-structured with a purpose statement, details paragraph, Args section, returns summary, and examples. Slightly verbose but 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?

Covers purpose, parameters, return format, and examples. Lacks details on pagination or limits, but is sufficient for a scanning tool with no output schema.

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?

With 0% schema description coverage, the description fully compensates by providing clear, explanatory text for each parameter, including defaults, auto-discovery, and example values.

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?

Clearly states the tool scans for cloud cost waste patterns using a proprietary pattern library, covering multiple categories and returning structured findings with confidence and waste estimates. Distinguishes from siblings like 'audit_duplicate_spend' by focusing on broad waste detection.

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?

Provides examples of usage and parameter descriptions, but lacks explicit guidance on when to use this tool versus alternatives or when not to use it. No comparison with sibling tools.

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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