Loop Engineering.
Loop Engineering helps you write instructions for AI coding agents that know when to stop.
Project overview
The short version
Loop Engineering helps you write instructions for AI coding agents that know when to stop. The goal generator starts from a task type, such as CI fix, bug fix, PR review, SEO content refresh or data cleaning, and a target tool, such as Claude Code, Codex, Cursor, GitHub Actions or Ralphify. It fills in a hypothesis, an objective, where the agent should look first, a validation command, the evidence to capture and an independent checker, then outputs a copyable goal in formats like a Claude or Codex /goal or a RALPH.md file. Each output spells out boundaries, such as not deleting tests or bypassing lint, a stop rule with a maximum iteration count, a budget line, a fallback summary and human approval before merging, deploying or spending money. The site also has templates, a skills directory, a token budget calculator and a Readiness Doctor that scores a pasted workflow. It's free with no sign-up, the privacy policy says tool inputs stay in your browser, and it's run independently by TianMingAI with no affiliation to the agent vendors.
Project facts
Project details
- Category
- Developer Tools
- Type
- Not listed
- Platforms
- See Project Note
- Pricing
- See Project Note
- Availability
- Other
- Published
- Oct 28, 2026
Details come from the published Project Note and named sources. Check the project site for current terms. The Note may have more context when a fact isn't recorded here.
Before you visit
Good to know
Built for
- Developers running Claude Code, Codex, Cursor or GitHub Actions agents on repeatable tasks like CI fixes and PR reviews.
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