coding-pipeline
Enforces a disciplined 4-phase pipeline for non-trivial coding tasks: Plan (hypothesis) → Code (one fix) → Validate (root cause) → Debug (max 3 tries, escalate). Prevents blind patching, symptom fixes, and retry loops. Activate for any bug fix, feature implementation, refactor, or error investigation that isn't a trivial one-line change.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/brasco05/coding-pipelineCoding 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:
- Task breakdown — what is actually being asked? Break into the smallest independent units.
- Hypothesis — one sentence in the form: "I believe [symptom] is caused by [cause], because [evidence]."
- Scope — which files/modules are in-bounds, which are explicitly out-of-bounds
- 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.
Metadata
Not sure this is the right skill?
Describe what you want to build — we'll match you to the best skill from 16,000+ options.
Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-brasco05-coding-pipeline": {
"enabled": true,
"auto_update": true
}
}
}Related Skills
auto-dream
Memory consolidation skill that replicates Anthropic's Auto Dream feature. Runs a 4-phase reflective pass over memory files: Orient → Gather → Merge → Prune. Use when: (1) Context window feels cluttered with stale info, (2) After long coding sessions, (3) Manually triggered with /dream, (4) Automatically after daily-reflection. Keeps memories tight, removes contradictions, converts relative dates to absolute.
daily-reflection
Daily reflection routine that runs automatically via cron job at 23:59. Analyzes the day, extracts learnings, updates solution memory, detects recurring patterns, and prepares a morning briefing. Use when: (1) setting up automated end-of-day reflection, (2) building long-term agent memory and learning systems, (3) creating morning briefings for the next day. Trigger phrases: 'daily reflection', 'end of day summary', 'reflect on today', 'update solution memory'.
Deep Debugging
Skill by brasco05
keyword-research
Multi-source keyword intelligence and autocomplete research. Fetches real-time suggestions from Google, YouTube, Amazon, and DuckDuckGo — no API key required. Use when: (1) doing SEO or content keyword research, (2) finding what users search for on a topic, (3) competitor or niche research, (4) expanding a seed keyword into hundreds of related terms, (5) building keyword lists for ads or content. Triggers on: keyword research, what do people search for, autocomplete, keyword ideas, SEO keywords, search suggestions, keyword list.
ollama-memory-setup
Sets up local semantic memory search for OpenClaw using Ollama + nomic-embed-text. Use when: (1) memory_search returns 'node-llama-cpp is missing' or 'Local embeddings unavailable' error, (2) user wants local/private embeddings without external API keys (OpenAI, Gemini, Voyage), (3) setting up memory search for the first time on macOS or Linux, (4) node-llama-cpp fails to install or build. Fixes the common node-llama-cpp installation failure by routing through Ollama's OpenAI-compatible embedding API instead of a local binary.