Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLIVVS CodeWWindsurf+15 more

    Agent Spend Guardrails

    1

    Define spending rules for your AI agent — caps, category whitelists, approval thresholds — and audit what it bought or almost bought, with an approve/hold/block verdict per transaction.

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    See it in action

    You say

    I'm about to let my agent buy software and cloud services. Set up balanced spend guardrails, then audit these attempts: $20 OpenAI API credits; $55 AWS; $38 Figma (new merchant); $300 AWS single charge; $90 Delta flight.

    Your agent does

    POLICY (Balanced): per-txn $75 | approval threshold $40 | hard ceiling $250 | monthly cap $500 | categories {software, API credits, cloud, domains} | merchants {OpenAI, AWS, Cloudflare, Namecheap}

    VERDICTS | Amount | Category | Merchant | Verdict | Binding rule | Reason | | $20 | API credits | OpenAI | APPROVE | auto band | Whitelisted, under $40 threshold | | $55 | cloud | AWS | HOLD | approval threshold | Whitelisted but >= $40, needs yes | | $38 | software | Figma | HOLD | new merchant | Under threshold but unlisted merchant | | $300 | cloud | AWS | BLOCK | hard ceiling | Exceeds $250 single-txn ceiling | | $90 | travel | Delta | BLOCK | category whitelist | Travel not in scope |

    REMEDIATION: Add Figma if intended; split the $300 AWS charge or raise the ceiling deliberately; add a travel category with its own cap if now in scope.

    HEADLINE: "1 approved, 2 held for review, 2 blocked — $503 in attempted spend gated; $20 auto-approved."

    What you get

    Audit what your agent bought or almost boughtDecide what needs human approval vs. autonomousBuild a reusable spend policy for any agentSet spending rules before letting an agent buy

    About this skill

    Agentic checkout and agent-to-agent payment rails (x402, AP2, and the wave behind them) are about to let AI agents spend real money on your behalf. The moment that happens, you want controls — before the agent acts, not regret after the wrong $800 flight is booked.

    Agent Spend Guardrails turns loose intent ("don't overspend") into an explicit, enforceable spend policy: per-transaction caps, rolling daily/weekly/monthly caps, category whitelists, merchant whitelists, and an approval-threshold ladder that decides what the agent may do alone versus what needs a human yes. It then audits what your agent bought — or almost bought — against that policy and returns a clear per-transaction verdict: APPROVE, HOLD, or BLOCK, each with the binding rule and a one-line reason.

    It is built to fail safe: anything ambiguous defaults to HOLD or BLOCK, never auto-approve. New merchants, off-whitelist categories, foreign currency, non-refundable charges, and cap proximity all escalate toward human review. The output is a compact policy block, a verdict table, a short remediation list, and a one-line headline you can screenshot.

    The package is a lean SKILL.md orchestrator plus a bundled REFERENCE.md containing the full rule schema, three approval-ladder templates (conservative/balanced/permissive), a trigger catalog, worked examples, and a ready-to-fill report template.

    This skill defines and audits policy only. It never executes, authorizes, or moves money, holds no payment credentials, and is decision support — not financial advice. A human owns every real-money decision.

    How to install

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

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