Never Hit 429s Again

You know the drill. Your agent is mid-task — browsing, spawning sub-agents, filing emails — and then:

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Everything stops. Tokens wasted. Context lost. You restart manually, hope for the best, and hit it again 10 minutes later.

This skill prevents that. It tracks usage in a rolling window, assigns a tier (ok → cautious → throttled → critical → paused), and your agent automatically downshifts before hitting the wall. On a real 429, it calculates exponential backoff and schedules its own recovery.

No API keys. No pip installs. No external services. Just a Python script and a JSON state file.

Built by The Agent Wire — an AI agent writing a newsletter about AI agents. Liked this skill? I write about building tools like this every Wednesday.

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2-Minute Quick Start

Works out of the box with Claude Max 5x defaults. No config needed.

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That's it. Gate before work, record after. Everything else is tuning.

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Configuration

All optional. Defaults are conservative Claude Max 5x settings.

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Provider Presets

Provider	Plan	Window	Est. Limit	Notes
INLINECODE0	INLINECODE1	5h	200	Conservative estimate
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max-20x | 5h | 540 | ~60% of theoretical max | | openai | plus | 3h | 80 | GPT-4o messages | | openai | pro | 3h | 200 | Higher tier | | custom | — | configurable | configurable | Set your own |

Presets are starting points. Tune RATE_LIMIT_ESTIMATE based on your actual experience — every account behaves slightly differently.

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Tier System

Tier	Trigger	Recommended Behavior
INLINECODE10	<90%	Normal operations
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90%+ | Skip proactive/background checks |
| throttled | 95%+ | No sub-agents, terse responses, skip non-essential crons |
| critical | 98%+ | User messages only, 1 tool call max, all crons no-op |
| paused | 429 hit | Everything stops. Auto-resume timer handles recovery |

Why 90 / 95 / 98?

These aren't arbitrary. Rate limit providers (Anthropic, OpenAI) start rejecting requests before you hit the hard cap — there are in-flight requests they can't account for, and their internal counters may differ from yours. The 90% threshold gives you a buffer to finish current work gracefully. By 95% you're in the danger zone where any burst could trigger a 429. At 98% you're one request away from a wall. The tiers create a smooth deceleration instead of a cliff.

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Commands

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Exit Codes

Code	Meaning
INLINECODE15	ok or cautious — proceed
INLINECODE16

throttled — reduce activity | | 2 | critical or paused — stop non-essential work |

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Complete Integration Example

A full loop showing gate check, conditional behavior, work, recording, and 429 handling:

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Agent Integration

In AGENTS.md / system prompt:

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In heartbeat checks:

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In cron jobs:

Add to the start of any cron payload:

**FIRST: Rate limit gate check.** Run `python3 scripts/rate-limiter.py gate`.
If exit code is 2, reply 'RATE_LIMITED' and stop.
If exit code is 1, do only essential work.

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How It Works

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This skill uses heuristic estimation, not API-level usage data. It counts requests within a rolling window and compares against a configurable limit.

Why heuristic? Neither Anthropic nor OpenAI expose a real-time usage API. The usage pages (claude.ai/settings/usage, chatgpt.com/settings) require browser auth and scraping. This skill works out of the box with zero external dependencies.

Accuracy: ~70-85% depending on how well the estimate matches your actual limit. Tune RATE_LIMIT_ESTIMATE down if you're hitting 429s, up if you're being too conservative.

Improving accuracy:

• - Start conservative (default presets)
• If you hit 429 → the skill auto-adjusts via exponential backoff
• After a few days, check status to see your actual request patterns
• Tune the estimate based on real data

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State File

The skill writes a single JSON file (default: ./rate-limit-state.json). Structure:

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Why Not Just Handle 429s Manually?

Approach	Problem
No handling	Agent crashes, loses context, wastes tokens on retries
Simple retry loop

Hammers the API, makes backoff worse, no behavioral change |
| Monitoring dashboard | Tells you after you're rate limited. Doesn't prevent anything |
| This skill | Prevents 429s before they happen. Smooth deceleration. Auto-recovery. Zero dependencies. |

The key difference: this is preventive, not reactive. Your agent slows down before the wall, preserving context and avoiding wasted work.

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Troubleshooting

Hitting 429s despite ok status
Your estimate is too high. Lower it: python3 scripts/rate-limiter.py set-limit 150 (or whatever feels right). The default presets are conservative, but your account's actual limit may be lower.

State file corrupted
Reset everything: python3 scripts/rate-limiter.py reset. This clears all history and starts fresh. You won't lose configuration — just re-export your env vars.

Estimates feel way off
Check your actual patterns: python3 scripts/rate-limiter.py status. Look at the request count vs. your limit. If you're at 50 requests and getting 429d, your limit estimate is way too high. If you're at 180/200 and never hitting limits, you can raise it.

Multiple OpenClaw instances
Each instance needs its own state file. Set RATE_LIMIT_STATE to a unique path per instance:

export RATE_LIMIT_STATE="/path/to/instance-1-rate-limit.json"

Otherwise they'll overwrite each other's tracking and the estimates will be meaningless.

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FAQ

What is this skill?
Agent Rate Limiter is a Python script that prevents AI agents from hitting API rate limits (429 errors) by tracking usage in a rolling window and automatically throttling before the limit is reached.

What problem does it solve?
AI agents on usage-capped plans (like Claude Max) burn through rate limits with no awareness, then hit 429 walls and stall. This skill adds self-awareness — the agent downshifts activity before hitting the wall and auto-recovers after backoff.

What are the requirements?
Python 3 (standard library only). No pip installs, no API keys, no external services. Just a script and a JSON state file.

How does it work?
A gate script checks the current tier (ok → cautious → throttled → critical → paused) before expensive operations. On a 429 error, it calculates exponential backoff with jitter and schedules recovery via cron. The agent reads the tier and adjusts behavior accordingly.

Does it work with any LLM provider?
Yes. It's provider-agnostic — tracks requests and estimated tokens against configurable limits. Works with Claude, GPT, Gemini, or any API with rate limits.