Agents Agent Loop Guardrails

---
name: agents-agent-loop-guardrails
description: "Bound agent autonomy with step budgets, spend caps, human gates, and checkpointing so failures stay cheap and debuggable."
---
# Add guardrails to autonomous agent loops

> Bound agent autonomy with step budgets, spend caps, human gates, and checkpointing so failures stay cheap and debuggable.

**Track:** 🤖 AI Engineering · **Domain:** AI Agents · **Level:** advanced · **~45 min**

**Who this is for:** AI Engineers, ML Engineers, LLM App Developers, Agent Builders

## When to Use This Skill

Bound agent autonomy with step budgets, spend caps, human gates, and checkpointing so failures stay cheap and debuggable.
Use it whenever a matching task appears in conversation — the agent loads these instructions on demand.

## Steps

1. Set hard max-step and max-token budgets; treat exhaustion as a normal outcome
2. Checkpoint full state after every step so runs resume or replay cleanly
3. Require explicit human approval before irreversible external actions
4. Detect loops: identical tool+args twice means intervene or abort
5. Emit structured events per step for tracing and postmortems
6. Run a canary suite of risky tasks nightly and alert on behavior drift

## Common Pitfalls

- Unbounded retry loops burning budget on a failing subgoal
- Approving via broad allowlists instead of per-action gates

## Success Signals

- Mean steps-to-completion trending down
- 100% of destructive actions behind approval

## Commands

**Install with skills CLI**
```bash
npx skills add aniruddhaadak80/skills --skill agents-agent-loop-guardrails
```

**Install globally**
```bash
npx skills add aniruddhaadak80/skills --skill agents-agent-loop-guardrails -g
```

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Part of [aniruddhaadak80/skills](https://github.com/aniruddhaadak80/skills) · Browse all at https://skills.sh/aniruddhaadak80/skills