claudeers.

🔓 unclaimed — this page was auto-generated from GitHub. Are you the creator?

Claim this page →
// Automation & Workflows

claude-eng-loop

Engineering Loop — a CLAUDE.md workflow template that turns AI coding agents into structured engineers: 9-phase process from task intake to goal verification…

Actively maintained
97/100
last commit 15 days ago
last release none
releases 0
open issues 0
// install
git clone https://github.com/sidan93/claude-eng-loop

🤖 Claude Engineering Loop

A structured process for Claude Code — phases, planning, verification, escape hatches.


The problem

If you let Claude Code run autonomously, it code-dumps without a clear goal, forgets its own context, and declares victory before verifying the results. You end up debugging AI-generated bugs instead of shipping features.

This is a drop-in CLAUDE.md template that defines a mandatory planning process, hard limits on retry loops, and an automatic escape hatch before Claude burns through your API credits.


🎯 What this does

A single CLAUDE.md file that defines a mandatory 9-phase process for every task:

Receive → Understand → Decompose → Plan → Align → Execute → Verify → [Gap? → Plan]

Key behaviors it defines:

  • Agent confirms understanding with you before touching any code
  • Every task is broken into blocks, each with an explicit plan
  • Plans are reviewed for coherence before execution starts
  • Execution is verified against the original goal — not just "it compiles"
  • Infinite retry loops are cut off with a hard escape hatch
  • Human confirmation gates can be disabled for fully autonomous runs

🗺️ How it works

flowchart TD
    START([🆕 New Task]) --> QA{Pure knowledge\nquestion?\nNo code · no action}
    QA -->|✅ Yes| ANSWER([💬 Direct Answer])
    QA -->|No| INIT[Session Init\nInteractive · Autonomous · Just Chat?]
    INIT -->|Just Chat| CHAT([💬 Just Chat\nLoop suspended])
    INIT -->|Interactive or Autonomous| P0[Phase 0: Receive\nGather all context]
    P0 --> P1[Phase 1: Understand\nRestate & confirm goal]
    P1 --> TRACK{Micro-task?\nAll criteria met?}

    TRACK -->|✅ Fast Track| EX_FT[Phase 6: Execute]
    TRACK -->|Full Loop| P2[Phase 2: Decompose\nBreak into blocks]

    P2 --> P3[Phase 3: Plan\nMax 5–7 steps per block]
    P3 --> P4[Phase 4: Review\nCoherence check]
    P4 --> P5[Phase 5: Align\nPresent plan → approve]
    P5 --> P6[Phase 6: Execute\nBlock by block]

    EX_FT --> P7
    P6 --> P7[Phase 7: Verify\nTests · scenario · plan vs result]
    P7 --> P8[Phase 8: Goal Check\nOriginal goal achieved?]

    P8 -->|✅ Yes| DONE([🏁 Done])
    P8 -->|❌ Gap found| ESC{Escape Hatch\ntriggered?}

    ESC -->|No — iteration ≤ 3| P3
    ESC -->|Yes| STOP([🛑 Stop & Escalate\nReport to human])

    style STOP fill:#ff4444,color:#fff
    style DONE fill:#22c55e,color:#fff
    style ANSWER fill:#94a3b8,color:#fff
    style CHAT fill:#94a3b8,color:#fff
    style START fill:#6366f1,color:#fff
    style TRACK fill:#f59e0b,color:#fff
    style ESC fill:#f59e0b,color:#fff
    style QA fill:#f59e0b,color:#fff

🚀 Quick Start

curl -o CLAUDE.md https://raw.githubusercontent.com/sidan93/claude-eng-loop/main/CLAUDE.md

Review the file, fill in the ## Project Context section, then launch Claude Code and give it a task. It will ask how to proceed before touching anything.


💬 Direct Answer for pure questions

Asking about a concept, tool, or technology — not this project? The agent answers immediately, no phases, no tracking:

  • "What is prompt caching?" → Direct Answer
  • "How does git rebase work?" → Direct Answer
  • "How should we handle this in our codebase?" → Loop (has an action implication)
  • "Why is this code slow?" → Loop (debugging task)

The check is strict: if the question references the project, contains any action word (fix, add, check, review…), or could produce a follow-up task — the Loop runs as usual.


⚡ Fast Track for micro-tasks

Fixing a typo? Renaming a variable? The agent detects micro-tasks and skips heavy planning:

Receive → Understand → Execute → Verify

Criteria: single self-contained change, no architectural decisions, no ambiguity, under 5 minutes. Everything else gets the full loop.


🔧 Execution modes

At the start of each task, the agent asks once (with clickable options if your environment supports it):

ModeWhen to useWhat happens
Interactive (default)Unclear requirements, high stakesAgent confirms understanding and plan before each key step
AutonomousWell-defined task, you want to step awayAgent proceeds without approvals, stops only on hard blockers
Just ChatQuestions, exploration, brainstormingLoop suspended — agent answers directly, no phases or planning

Two independent settings for fully autonomous runs:

  • CLAUDE.md Autonomous mode (chosen at session start) — controls whether the agent waits for approval at phase gates
  • Claude Code Auto mode (Shift+Tab to cycle) — controls whether Claude prompts for permission on each file edit or shell command

Both can be set independently. Autonomous mode without Auto mode still prompts on each file/shell action. Auto mode without Autonomous mode still pauses at phase gates.

Security: Claude Code Auto mode lets Claude act without per-action confirmation. Use only in isolated environments — never with access to production systems or credentials.


🛡️ Escape hatch

The loop never runs forever. Claude stops and asks you when:

  • The same gap appears twice across iterations
  • A block fails more than twice
  • The root cause is outside Claude's control (third-party bug, missing access, changed requirements)
  • More than 3 full loop iterations complete without reaching the goal

📋 The 9 phases

PhaseWhat happens
0 — ReceiveRead the full task and all linked context before forming any opinion
1 — UnderstandRestate the task; confirm with you (interactive) or document and proceed (autonomous)
2 — DecomposeBreak into independently plannable blocks
3 — PlanWrite an explicit step-by-step plan for each block (max 5–7 steps)
4 — ReviewRead all plans together, check coherence against the original goal
5 — AlignSummary for simple tasks; full plans for complex ones; wait for approval or proceed per mode
6 — ExecuteRun block by block using available tools and skills
7 — VerifyTests, core scenario, plan vs. result — mandatory before declaring done
8 — Goal checkDid we achieve what was actually asked? If not — gap analysis, back to Phase 3

💰 Token usage

The goal isn't to save tokens — it's to actually achieve what you asked for. Without structure, Claude produces output. With the loop, Claude produces the right output.

Catching a wrong approach in Phase 3 is cheaper than unwinding it after Phase 6.

  • Interactive mode is cost-efficient — you review plans before the model executes, so errors are caught early
  • Autonomous mode can be expensive on large or ambiguous tasks — iterative gap analysis multiplies context fast. Use it on tightly scoped tasks. Set a budget limit in Claude Code settings before running autonomously
  • Plan verbosity is capped at 5–7 steps per block by default

📦 Setup options

Per-project (recommended): drop CLAUDE.md into your repo root and fill in ## Project Context. Pay special attention to Off-limits — this is what prevents Claude from touching production databases, force-pushing main, or doing anything irreversible without review.

Global (all projects): place CLAUDE.md in ~/.claude/ and remove the ## Project Context section — it has no meaning at the global level.

ScopeLocationProject Context
Global~/.claude/CLAUDE.mdRemove it
Per-project<repo-root>/CLAUDE.mdFill it in

Both can coexist: global sets the process, per-project overrides with specifics. Claude Code loads global config first, project config second — later instructions win for the same topic.

Existing CLAUDE.md: paste the Engineering Loop content before or after your existing instructions. Project-specific instructions take priority over the loop.


🛠️ Works with

  • Bare Claude Code — no extra setup required
  • MCP servers (Jira, GitLab, Figma, Confluence, etc.) — the loop tells the agent when and how to use them
  • Superpowers plugin — skill references map directly to Superpowers skills; without it, they describe the approach to take manually

⚠️ Probabilistic, not deterministic

The Engineering Loop is a process guide, not an enforcement system. LLMs follow instructions reliably in most cases — but a capable model with extended thinking can rationalize skipping phases when a task looks "obvious". The model reads the instructions, understands them, and still decides they don't apply right now.

This is a known property of instruction-following in LLMs, not a bug in the template.

To maximize compliance:

  • Mention the loop explicitly in your prompt. "Follow the Engineering Loop" or "start with the mode question" in the task message significantly improves compliance — the instruction is fresh in context when the model starts reasoning.
  • Interrupt when phases are skipped. If the agent jumps straight to coding, stop it: "You're skipping the loop — go back to Phase 0." Self-correction works well once the model is reminded.
  • Fresh sessions help. A model mid-session with lots of context is more likely to shortcut. Start a new session for significant tasks.
  • Avoid conflicting plugins. Any plugin that instructs the model to "act immediately before any response" competes with the mode question. The loop works best without aggressive system-level plugins.

The loop works as a shared contract between you and the agent. When both sides reference it, compliance is high. When only the file does, it's probabilistic.


🔍 How to verify the loop is working

Claude should name the current phase at each transition. If it silently jumps to writing code — it's not following the loop.

Signs it's working:

  • First message asks "Interactive, Autonomous, or Just Chat?"
  • Responses mention phases: "Phase 0: reading the ticket...", "Phase 3: writing plans..."
  • Micro-tasks get: "Fast Track: [reason]. Skipping Phases 2–5."
  • In Just Chat mode: no phases mentioned — that's correct, not broken

Signs it's not: starts coding immediately without asking the mode question, never mentions phases in Interactive/Autonomous, declares done without verifying.

If it skips phases: this is expected occasionally — see the Probabilistic section above. Interrupt and redirect: "Stop. You skipped the loop. Ask me for mode and restart from Phase 0." The model knows the rules and self-corrects well when prompted directly.


✏️ Customization

The loop is intentionally generic. Extend it in your CLAUDE.md:

  • Add project-specific steps per phase ("in Phase 6, always run make lint before committing")
  • Override parallelism rules for your stack
  • Add domain-specific escape hatch conditions
  • Replace generic skill references with concrete tool names

License

MIT

// compatibility

Platformsapi
Operating systems
AI compatibilityclaude
LicenseMIT
Pricingopen-source
Language

// faq

What is claude-eng-loop?

Engineering Loop — a CLAUDE.md workflow template that turns AI coding agents into structured engineers: 9-phase process from task intake to goal verification, with execution modes, escape hatches, and project context scaffold. Works with any toolset — Claude Code, MCP servers, Superpowers.. It is open-source on GitHub.

Is claude-eng-loop free to use?

claude-eng-loop is open-source under the MIT license, so it is free to use.

What category does claude-eng-loop belong to?

claude-eng-loop is listed under devtools in the Claudeers registry of Claude-compatible tools.

2 views
10 stars
unclaimed
updated 14 days ago

// embed badge

claude-eng-loop on Claudeers
[![Claudeers](https://claudeers.com/api/badge/claude-eng-loop.svg)](https://claudeers.com/claude-eng-loop)

// retro hit counter

claude-eng-loop hit counter
[![Hits](https://claudeers.com/api/counter/claude-eng-loop.svg)](https://claudeers.com/claude-eng-loop)

// reviews

// guestbook

0/500

// related in Automation & Workflows

🔓

The agent that grows with you

// automationNousResearch/Python211,605MIT[ claude ]
🔓

The API to search, scrape, and interact with the web at scale. 🔥

// automationfirecrawl/TypeScript143,720AGPL-3.0[ claude ]
🔓

🌐 Make websites accessible for AI agents. Automate tasks online with ease.

// automationbrowser-use/Python103,709MIT[ claude ]
🔓

An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message…

// automationbytedance/Python76,016MIT[ claude ]
→ see how claude-eng-loop connects across the ecosystem