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    business-ai-governance-mesh

    business-ai-governance-mesh

    A modular governance framework for AI policy, agent risk assessment, human-in-the-loop approvals, and audit trails.

    Updated Jun 2026
    107 views
    Security scanned

    $7

    · or 35 credits

    30-day refund guarantee

    Secure checkout via Stripe

    Included in download

    • Standardize AI use policies across engineering and product teams.
    • Assess if an AI agent task requires human-in-the-loop approval.
    • terminal automation included
    • Includes example output and usage patterns
    • Instant install

    Sample input

    Assess the risk for finance-agent-01 to update the ledger using an external API with a payload containing customer PII.

    Sample output

    STATUS: needs_approval RISK SCORE: 7/10 (High) DATA EXPOSURE: PII detected in prompt payload. REASON: Task involves an external API and irreversible financial data modification. REQUIRED GATE: Human supervisor approval needed for 'finance-agent-01' to modify the ledger.

    Screenshots

    About This Skill

    Enterprise-Grade AI Governance & Risk Management

    The Business AI Governance Mesh is a professional-grade skill designed for developers, architects, and compliance officers who need to implement structured oversight for AI agents and tools. It moves beyond simple prompting by enforcing a strict, artifact-gated workflow that ensures every AI action is policy-compliant and audit-ready.

    What it does

    This skill coordinates five critical governance modules—Policy, Risk, Approval, Audit, and Vendor Review—into a unified Mesh workflow. It transforms vague AI experiments into governed business processes by producing standardized artifacts like risk scores and data exposure maps.

    • AI Use Policy: Defines allowed, restricted, and prohibited behaviors for your team.
    • Agent Risk Assessment: Evaluates task safety, data sensitivity, and operational impact.
    • Human-in-the-loop Gates: Automatically identifies when a human must intervene before an agent proceeds.
    • Vendor Review: Assesses the risk of third-party APIs, LLM providers, and SaaS plugins.
    • Audit Trails: Generates evidence-backed logs of every decision and approval for management review.

    Why use this skill?

    Standard LLM prompts often ignore context or fail to flag high-risk data exposures. This skill uses a "fail-closed" logic: if context is missing or risk is high, it blocks the action until requirements are met. It provides a formal verification report to prove that all governance gates have been cleared, making it ideal for regulated industries or internal security reviews.

    Use Cases

    • Standardize AI use policies across engineering and product teams.
    • Assess if an AI agent task requires human-in-the-loop approval.
    • Review third-party AI vendor risks before integrating new APIs.
    • Generate audit-ready evidence logs for security and management reviews.
    • Identify PII and data exposure risks in automated agent workflows.

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    Security Scanned

    Passed automated security review

    Permissions

    Terminal / Shell

    File Scopes

    business-ai-governance-mesh/**

    Compatible with SKILL.md-compatible agents such as Claude Code and Cursor.

    Frequently Asked Questions