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Coding Pipeline

作者 brasco05 · GitHub ↗ · v1.0.0 · MIT-0
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在 OpenClaw 中安装
/install coding-pipeline
功能描述
Enforces a disciplined 4-phase pipeline for non-trivial coding tasks: Plan (hypothesis) → Code (one fix) → Validate (root cause) → Debug (max 3 tries, escala...
使用说明 (SKILL.md)

Coding Pipeline

A disciplined 4-phase workflow for any non-trivial coding task. Each phase has a clear purpose, explicit exit criteria, and a loop-back rule when things go wrong. The phases exist because AI agents' default failure mode is blind iteration: edit → build → edit → build → give up. This skill forces hypothesis-driven work, one-fix-at-a-time discipline, root-cause verification, and bounded debugging.

This is a rigid skill — follow the phases exactly. Do not skip, merge, or reorder.

Core Rule

Every non-trivial task — bug fix, feature, refactor — goes through all 4 phases in order:

┌─────────────┐    ┌──────────┐    ┌───────────────┐    ┌─────────────┐
│  1 PLANNER  │───▶│ 2 CODER  │───▶│  3 VALIDATOR  │───▶│  4 DEBUGGER │
│ hypothesis  │    │ one fix  │    │ build + root  │    │ max 3 tries │
└─────────────┘    └────┬─────┘    └───────┬───────┘    └──────┬──────┘
       ▲                │                  │                   │
       │                │ unclear cause    │ fails             │ new hypothesis
       └────────────────┴──────────────────┴───────────────────┘
                        loop back to PLANNER

Skipping a phase or jumping straight to Phase 2 is the failure mode this skill prevents.

Quick Reference

Situation Active Phase Exit When
New task arrives Phase 1 Planner Hypothesis written, scope defined, success criteria explicit
Hypothesis validated Phase 2 Coder One focused change applied, no unrelated edits
Change applied Phase 3 Validator Build passes AND root cause verified
Validator fails Phase 4 Debugger Either fix found (→ Phase 2) or 3 attempts exhausted (→ escalate)
Unclear cause mid-fix Back to Phase 1 New hypothesis written
Fix introduces new error Back to Phase 1 Hypothesis was wrong

Phase 1 — Planner

Goal: Understand the task and formulate an explicit hypothesis before any code change.

Required outputs:

  1. Task breakdown — what is actually being asked? Break into the smallest independent units.
  2. Hypothesis — one sentence in the form: "I believe [symptom] is caused by [cause], because [evidence]."
  3. Scope — which files/modules are in-bounds, which are explicitly out-of-bounds
  4. Success criteria — how Phase 3 will verify this is fixed (not just the symptom gone)

Forbidden in Phase 1:

  • Editing any code
  • Running build or test commands to "see what happens"
  • Multiple parallel hypotheses — pick one, commit to it
  • Vague hypotheses ("something with the auth flow") — sharpen until specific

Exit criteria: Hypothesis is concrete, testable, and you can point to why this is the cause — not just what looks broken.

Loop-back trigger: If during Phase 2 or 3 the hypothesis turns out wrong, return here. Do not patch on top of a broken hypothesis.

See references/phase-1-planner.md for hypothesis patterns and scope breakdown templates.

Phase 2 — Coder

Goal: Apply exactly one focused change that tests the hypothesis from Phase 1.

Rules:

  1. One fix at a time — one change, one purpose, one file or one tightly-scoped set of files
  2. Full files, not snippets — deliver complete file contents when showing work
  3. No speculative refactoring — resist "while I'm in here…"; surgical scope only
  4. If the hypothesis is unclear mid-change → STOP, return to Phase 1

Definition of "one fix": A single logical change that either proves or disproves the hypothesis. Three unrelated improvements = three separate Planner → Coder → Validator cycles.

Exit criteria: Change is applied, diff contains only the intended work, nothing unrelated.

See references/phase-2-coder.md for scope discipline and loop-back triggers.

Phase 3 — Validator

Goal: Verify the change fixed the root cause, not just the symptom.

Checklist (adapt to stack):

  1. Build check — compile/transpile succeeds, no new errors
  2. Type check — no new type errors; any @ts-ignore / type: ignore needs an explicit written justification comment
  3. Focused test — run the specific test that proves the hypothesis, not the full suite
  4. Root-cause verification — the fix addresses the Phase 1 hypothesis, not a side effect
  5. Scope verification — diff matches what Phase 1 planned; no accidental changes
  6. Regression check — nothing adjacent broke

The symptom-vs-cause test:

If I rolled back this change, would the symptom return because of the same cause, or because of something else?

If you can't answer confidently, the fix is symptomatic. Go back to Phase 1.

Exit criteria: All checks pass, root cause verified, no regressions.

Failure → Phase 4 Debugger.

See references/phase-3-validator.md for stack-agnostic validation patterns.

Phase 4 — Debugger

Goal: Bounded debugging with documentation. Escalation over thrashing.

Hard rules:

  1. Max 3 attempts — after 3 failed fixes, STOP and escalate to the user
  2. Document every attempt — what was tried, what happened, why it failed
  3. Never repeat a fix — if attempt 1 failed, attempt 2 must be substantively different
  4. Never "just try again" — every attempt must be backed by a new hypothesis

Attempt log template (write to .pipeline-state/attempts-\x3Ctask>.md or inline in chat):

### Attempt N
- **Hypothesis**: What I now believe is wrong
- **Change**: What I modified (specific files/lines)
- **Result**: What happened (error output, unchanged behavior, new symptom)
- **Why it failed**: The actual root cause of this failure
- **Next direction**: What to try next OR escalate

After 3 failed attempts: STOP. Surface to the user with the full attempt log. Do not continue with a 4th attempt unless the user explicitly authorizes it.

Recovery trigger: If during Phase 4 a fundamentally new hypothesis emerges, return to Phase 1 — not Phase 2. A new hypothesis means a new cycle, not continued debugging.

See references/phase-4-debugger.md for escalation patterns and worked examples.

Phase Transition Gates

No phase transition is automatic. Each requires explicit criteria:

From To Required
1 → 2 Planner → Coder Hypothesis written + scope defined + success criteria
2 → 3 Coder → Validator One focused change applied, no unrelated edits
3 → Done Validator passes Build ✓ + types ✓ + root cause verified + no regressions
3 → 4 Validator → Debugger Any validation check failed
4 → 2 Debugger → Coder New hypothesis + change substantively different from previous attempts
4 → 1 Debugger → Planner Fundamentally new hypothesis (not incremental)
4 → STOP Debugger → Escalate 3 attempts exhausted
ANY → 1 Back to Planner Hypothesis proven wrong mid-cycle

Detection Triggers

Activate this pipeline automatically when the task is:

  • A bug report — user says something is broken
  • A feature request — non-trivial new functionality
  • A refactor — touching existing code for non-cosmetic reasons
  • An error investigation — digging into unexpected behavior
  • A test failure — a test that was passing now fails
  • A deployment issue — something that worked in dev fails in prod

Skip the pipeline only for:

  • Trivial edits (typo, formatting, one-line config)
  • Pure documentation changes
  • Explicitly exploratory work ("just experiment, don't commit")

Anti-Patterns

What this pipeline prevents:

  1. Symptom patching — fixing what looks wrong without understanding why
  2. Multi-fix chaos — changing three things at once, unable to tell which one worked
  3. Retry loops — trying the same fix with minor variations hoping it sticks
  4. Premature coding — jumping to Phase 2 before Phase 1 is done
  5. Validation skipping — "it compiles, ship it" without root-cause check
  6. Unbounded debugging — 8 attempts, no log, no escalation
  7. Speculative refactoring — "while I'm here, let me also clean up this other file"
  8. Hypothesis drift — quietly changing the hypothesis mid-fix to match what you just did
  9. Type-ignore laziness@ts-ignore without a written justification comment
  10. Scope creep — task was "fix login redirect", PR touches 14 unrelated files

See references/anti-patterns.md for concrete before/after examples of each.

Integration with Other Skills

This pipeline works well with — but does not replace — the following:

  • systematic-debugging — when Phase 4 escalates, hand off to systematic-debugging for the full investigation protocol
  • self-improving-agent — after every failed attempt in Phase 4, log to .learnings/ERRORS.md so the next task starts with that knowledge
  • root-cause-analysis — when Phase 3 root-cause verification is ambiguous, escalate to RCA
  • test-driven-development — Phase 1's "success criteria" naturally aligns with TDD's "write the failing test first"

See references/integration.md for detailed pairing patterns.

Platform Integration

Platform-specific activation and hook configuration lives in references/:

  • references/openclaw-integration.md — OpenClaw workspace setup, inter-session coordination
  • references/hooks-setup.md — Claude Code / Codex hook configuration (UserPromptSubmit)
  • references/multi-agent.md — Claude Code, Codex CLI, GitHub Copilot activation patterns

Best Practices

  1. Always start at Phase 1 — no shortcuts, no exceptions for "obvious" fixes
  2. One hypothesis, one fix — resist bundling
  3. Phase 3 verifies cause, not symptom — this is the hard check
  4. Phase 4 is bounded — 3 attempts, then escalate
  5. Document every failed attempt — pattern recognition matters
  6. Full files, no snippets — for reviewability
  7. Loop back to Planner on uncertainty — cheaper than debugging a wrong hypothesis
  8. Escalate fast — 3 failed attempts is a signal, not a suggestion

Source

This pipeline is based on a production coding standard used in NestJS/Next.js/PHP production systems. It emerged from repeated observation that AI agents, left to their defaults, retry-loop into incoherence on non-trivial work. The 4-phase structure + max-3-attempts rule + mandatory hypothesis is the minimum structure needed to keep agents disciplined.

安全使用建议
This skill appears coherent and aligned with its stated goal. Before installing: 1) Review the included scripts (scripts/activator.sh and scripts/phase-check.sh) if you want to ensure no automated execution in your environment; they are local helpers that create/modify .pipeline-state/. 2) If you do not want the pipeline text injected into every OpenClaw session, avoid installing into a shared workspace (install per‑project instead). 3) The skill recommends creating .pipeline-state/ and adding it to .gitignore — consider doing so to avoid committing local state. 4) Note the skill suggests handoffs to other skills (systematic-debugging, self-improving-agent) but does not automatically invoke remote services or require credentials. Overall this looks like a productivity discipline pack rather than a security risk.
功能分析
Type: OpenClaw Skill Name: coding-pipeline Version: 1.0.0 The 'coding-pipeline' skill bundle is a productivity framework designed to enforce a disciplined 4-phase workflow (Plan, Code, Validate, Debug) for AI coding agents to prevent 'retry loops' and 'symptom patching.' The included bash scripts (activator.sh and phase-check.sh) are simple, transparent utilities for state tracking and reminders within the local workspace. The skill instructions (SKILL.md) actually enhance safety by requiring the agent to document its logic and explicitly escalate to the user after three failed attempts, rather than continuing autonomously. No malicious code, data exfiltration, or prompt-injection attacks were found.
能力评估
Purpose & Capability
The name/description (enforce a 4‑phase coding pipeline) match the included materials: SKILL.md, templates, checklists, examples, and small helper scripts. Nothing in the repo requests unrelated capabilities (no cloud creds, no network download/install steps).
Instruction Scope
The SKILL.md instructs agents to write hypotheses, run builds/tests, and record Phase 4 attempt logs in a local .pipeline-state/ directory. Those actions are appropriate to a pipeline skill, but they do involve writing local state to the workspace and running developer build/test commands — expected for this purpose. There are no instructions to read secrets, call external endpoints, or exfiltrate data.
Install Mechanism
There is no remote install/download; the skill is instruction-first with optional local installation into an OpenClaw workspace. Package.json has no dependencies, and the included shell scripts are small and local-only. No high-risk download/extract steps are present.
Credentials
The skill declares no required environment variables, no credentials, and no config paths beyond creating a local .pipeline-state/ directory. That level of access is proportionate to the stated functionality.
Persistence & Privilege
OpenClaw integration recommends workspace injection so SKILL.md is loaded at session start; that makes the pipeline guidance present across sessions (intentional for this skill). The scripts create/write .pipeline-state/ in the workspace — a benign persistent artifact but one you should be aware of. The skill does not set always: true, does not require elevated privileges, and does not modify other skills' configs.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install coding-pipeline
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /coding-pipeline 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release introducing a structured 4-phase workflow for disciplined coding tasks. - Enforces a pipeline: Plan (hypothesis) → Code (one fix) → Validate (root cause) → Debug (max 3 tries, escalate) - Strictly prevents blind patching, retry loops, and symptom-only fixes. - Details explicit rules, exit criteria, and loop-back triggers for each phase. - Activates for bugs, features, refactoring, and any non-trivial coding change. - Includes anti-patterns and quick-reference tables for phase transitions and detection triggers.
元数据
Slug coding-pipeline
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Coding Pipeline 是什么?

Enforces a disciplined 4-phase pipeline for non-trivial coding tasks: Plan (hypothesis) → Code (one fix) → Validate (root cause) → Debug (max 3 tries, escala... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 98 次。

如何安装 Coding Pipeline?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install coding-pipeline」即可一键安装,无需额外配置。

Coding Pipeline 是免费的吗?

是的,Coding Pipeline 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Coding Pipeline 支持哪些平台?

Coding Pipeline 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Coding Pipeline?

由 brasco05(@brasco05)开发并维护,当前版本 v1.0.0。

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