Runaway Guard

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Enforces cost-safety discipline for paid AI and inference APIs by requiring explicit spending caps and execution bounds.

Runaway Guard is a specialized safety skill designed to prevent catastrophic 'bill shock' when working with paid AI services like Anthropic, OpenAI, and Fal.ai. It introduces cost as the third complexity dimension alongside time and space, ensuring that every API call site is protected by a documented 'wallet invariant.' By mandating pre-written cost contracts, concrete iteration bounds, and synchronized provider-side hard caps, this skill transforms risky unbounded loops and retry patterns into predictable, budget-safe implementations. It is essential for developers building autonomous agents, background jobs, or high-volume inference pipelines where a single logic bug could otherwise result in thousands of dollars in unintended charges.

Key Features

01Mandatory Cost Contracts: Requires explicit per-run and per-day spend limits before any API code is written.
02Concrete Iteration Bounds: Replaces theoretical loop termination with strict integer-based execution limits in code.
03132 GitHub stars
04Idempotency Enforcement: Mandates the use of idempotency keys for all mutating or charging calls to prevent double-billing.
05Concurrency & Fan-out Control: Limits parallel API requests to prevent unexpected spikes in billing and rate-limit hits.
06Multi-Layer Protection: Ensures code-level limits are backed by provider-dashboard hard caps to stop bleeding if code fails.

Use Cases

01Safeguarding background workers and webhook handlers against retry-induced cost spirals.
02Building autonomous LLM agents that self-reschedule or run in loops.
03Implementing image or media generation pipelines using billed-per-success APIs.