Finops Anomaly Intelligence

    by appugouda ai

    3

    Turn AWS billing mysteries into 10-minute root cause reports by correlating cost spikes with engineering events.

    Free

    4 installs5.0 (1 review)

    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLIVVS CodeWWindsurf+15 more

    See it in action

    You say

    Investigate why my AWS NAT Gateway costs spiked last week and link it to any recent infrastructure deployments or GitHub PRs.

    Your agent does

    HYPOTHESIS #1 [Confidence: HIGH | 87%] Root Cause: PR #4821 (@platform-team) removed S3 VPC Endpoint. Evidence: NatGatewayBytesOut +340% at 14:22 UTC matches PR merge time. Cost Delta: +$2,403 over 5 days. Monthly Projection: $18,240. Remediation: Re-add aws_vpc_endpoint.s3 to Terraform config.

    About this skill

    What it does

    FinOps Anomaly Intelligence is a root-cause analysis engine designed to investigate and resolve AWS cost spikes. It moves beyond simple alerts by cross-correlating AWS billing data (CUR/Cost Explorer) with engineering activities across GitHub, Jira, CloudWatch, and PagerDuty. At a high level, it detects the anomaly window, identifies impacted services, ranks root-cause hypotheses with confidence scores, and quantifies the "cost of inaction."

    Why use this skill

    Standard AWS alerts tell you that you spent too much, but they don't tell you why. Manually tracing a $10k spike through CloudTrail logs and PR history can take hours. This skill reduces that to 10 minutes. It is better than simple prompting because it uses a structured sequence of data extraction and correlation scripts to provide proof-based answers, not just hallucinations. It ensures developers see the financial impact of their code changes in real-time.

    Supported tools

    • Cloud: AWS (Cost Explorer, CUR, CloudWatch)
    • VCS/Task Management: GitHub Enterprise, Jira REST API
    • Observability/Ops: PagerDuty, Slack API
    • Frameworks: Boto3, Pandas, Python 3.10+

    What the output looks like

    The skill produces structured JSON data for workflows and human-readable Markdown reports. This includes a ranked Hypothesis Report linking specific PRs to dollar amounts, a Cost of Inaction table for executive reporting, and a pre-formatted Jira ticket ready for assignment to the responsible engineering team.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

    Reviews

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    4 people have installed this skill.

    Verified Download
    3 months ago
    Samuel Rose

    Trust & safety

    Security scanned

    Verified clean 3 months ago

    • Free to download with an account

    Installs4
    Listed3 months ago

    Creator

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