Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/S3YED/appie-kitnpx agentmods add skills/s3yed/appie-kit/autonomous-loopsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/s3yed/appie-kit/autonomous-loops)<a href="https://agentmods.dev/skills/s3yed/appie-kit/autonomous-loops"><img src="https://agentmods.dev/badge/skills/s3yed/appie-kit/autonomous-loops/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/s3yed/appie-kit/autonomous-loops"><img src="https://agentmods.dev/badge/skills/s3yed/appie-kit/autonomous-loops.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.05529 |
| Opus 5.5 | $0.00010 | $0.02212 |
| Sonnet 5.5 | $0.00005 | $0.01106 |
| Haiku 4.5 | $0.00003 | $0.00553 |
Grade A, and why
autonomous-loops scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to autonomous-loops — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 611 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autonomous Loops Skill
Compatibility note (v1.8.0):
autonomous-loopsis retained for one release. The canonical skill name is nowcontinuous-agent-loop. New loop guidance should be authored there, while this skill remains available to avoid breaking existing workflows.
Patterns, architectures, and reference implementations for running Claude Code autonomously in loops. Covers everything from simple claude -p pipelines to full RFC-driven multi-agent DAG orchestration.
When to Use
- Setting up autonomous development workflows that run without human intervention
- Choosing the right loop architecture for your problem (simple vs complex)
- Building CI/CD-style continuous development pipelines
- Running parallel agents with merge coordination
- Implementing context persistence across loop iterations
- Adding quality gates and cleanup passes to autonomous workflows
Loop Pattern Spectrum
From simplest to most sophisticated:
| Pattern | Complexity | Best For |
|---|---|---|
| Sequential Pipeline | Low | Daily dev steps, scripted workflows |
| NanoClaw REPL | Low | Interactive persistent sessions |
| Infinite Agentic Loop | Medium | Parallel content generation, spec-driven work |
| Continuous Claude PR Loop | Medium | Multi-day iterative projects with CI gates |
| De-Sloppify Pattern | Add-on | Quality cleanup after any Implementer step |
| Ralphinho / RFC-Driven DAG | High | Large features, multi-unit parallel work with merge queue |
1. Sequential Pipeline (claude -p)
The simplest loop. Break daily development into a sequence of non-interactive claude -p calls. Each call is a focused step with a clear prompt.
Core Insight
If you can't figure out a loop like this, it means you can't even drive the LLM to fix your code in interactive mode.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 611 lines · 26 tokens per session scan A 25431f497ec2
autonomous-loops is a skill published in the GitHub repository S3YED/appie-kit (12 stars, last pushed 1mo ago), licensed MIT. It adds 26 tokens to every session and 5,529 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to autonomous-loops, differing in 0 lines, and is treated as a copy.
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