Overview
- Skill Key
- brothaakhee/superclaw
- Author
- brothaakhee
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/brothaakhee/superclaw
- Latest Commit SHA
- ee7a10291b959e43f22c5a14739413dbe0909333
Complete software development workflow enforcing design → plan → execution with checkpoints
Stars
0
Installs
0
Status
ACTIVE
Visibility
PUBLIC
直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 superclaw 技能。 若已安装,则直接安装 superclaw 技能。
# Superclaw ⚔️
**Disciplined software development workflow for OpenClaw agents**
Based on [obra/superpowers](https://github.com/obra/superpowers) by Jesse Vincent.
---
## What This Skill Package Does
Superclaw prevents your agent from jumping straight into code. It enforces a three-phase workflow:
1. **🧠 Brainstorming** (`brainstorming/SKILL.md`) — Design before code
2. **📋 Writing Plans** (`writing-plans/SKILL.md`) — Plan before implementation
3. **⚙️ Executing Plans** (`executing-plans/SKILL.md`) — Batched execution with checkpoints
All three skills chain automatically when building software.
---
## How It Works
### Phase 1: Brainstorming (Design Before Code)
**Triggers:** When creating features, building components, adding functionality
**Process:**
1. Check context (MEMORY.md, USER.md, daily logs)
2. Ask Socratic questions (requirements, constraints, trade-offs)
3. Propose 2-3 approaches with pros/cons
4. Present design
5. Get approval
6. Save design document to `workspace/docs/plans/YYYY-MM-DD-<topic>-design.md`
7. **Automatically invoke writing-plans skill**
**Hard Gate:** No code until design approved.
---
### Phase 2: Writing Plans (Plan Before Implementation)
**Triggers:** When you have an approved design
**Process:**
1. **ASK about methodology** (TDD? Direct implementation?)
2. Ask about commit frequency
3. Break work into 2-5 minute tasks
4. Save implementation plan to `workspace/docs/plans/YYYY-MM-DD-<topic>-plan.md`
5. **Automatically invoke executing-plans skill**
**Key Feature:** Questions, not mandates. Respects user preferences and time constraints.
---
### Phase 3: Executing Plans (Batched Execution with Checkpoints)
**Triggers:** When you have an implementation plan
**Process:**
1. Load plan from document
2. Batch tasks into groups of 3-5
3. Execute batch (using `sessions_spawn` for isolation)
4. Review outputs
5. Checkpoint ("Batch N complete. Continue?")
6. Update `memory/YYYY-MM-DD.md` with progress
7. Repeat until com...
# Superclaw ⚔️ **A complete software development workflow for OpenClaw agents** Superclaw enforces discipline through three chained skills: design before code, plan before implementation, batched execution with checkpoints. Based on [obra/superpowers](https://github.com/obra/superpowers) by Jesse Vincent, adapted for OpenClaw's personal assistant architecture. --- ## What It Does Your agent doesn't just jump into code. It: 1. **🧠 Brainstorms with you** — Socratic questions, design proposals, approval before coding 2. **📋 Writes TDD-ready plans** — Breaks work into 2-5 minute tasks (with methodology questions, not mandates) 3. **⚙️ Executes in batches** — Groups tasks, checkpoints between batches, updates memory --- ## Installation (Future) ```bash openclaw hub install superclaw ``` Skills auto-load when relevant tasks are detected. --- ## Skills Included ### 1. Brainstorming (`brainstorming/SKILL.md`) **Enforces design-before-code** - **Triggers:** When creating features, building components, adding functionality - **Hard Gate:** No code until design approved - **Process:** Context check → Questions → Approaches → Design → Approval → Save - **Then:** Automatically invokes writing-plans skill **Example:** ``` User: "Build a todo CLI" Agent: [Asks questions about storage, features] Agent: [Proposes 2-3 approaches with trade-offs] Agent: [Presents design, gets approval] Agent: [Saves design doc, invokes writing-plans] ``` ### 2. Writing-Plans (`writing-plans/SKILL.md`) **Enforces plan-before-implementation** - **Triggers:** When you have an approved design - **Key Feature:** ASKS about methodology (TDD? Commit frequency?) instead of mandating - **Process:** Ask methodology → Break into tasks → Save plan - **Then:** Automatically invokes executing-plans skill **Example:** ``` Agent: "Should we use TDD (tests first) or direct implementation?" User: "Direct implementation" Agent: [Creates plan with 10 tasks, 2-5 min each] Agent: [Saves plan doc, invok...
heyixuan2
Bambu Lab 3D printer control and automation. Activate when user mentions: printer status, 3D printing, slice, analyze model, generate 3D, AMS filament, print monitor, Bambu Lab, or any 3D printing task. Full pipeline: search → generate → analyze → colorize → preview → open BS → user slice → print → monitor. Supports all 9 Bambu Lab printers (A1 Mini, A1, P1S, P2S, X1C, X1E, H2C, H2S, H2D).
edholofy
University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning required.
lethehades
macOS WPS Office workflow helper skill for safer document preparation, conversion, export, and compatibility guidance
capt-marbles
Generative Engine Optimization (GEO) for AI search visibility. Optimize content to appear in ChatGPT, Perplexity, Claude, and Google AI Overviews. Use when optimizing websites, pages, or content for LLM discoverability and citation.
carlulsoe
Local speech-to-text with NVIDIA Parakeet TDT 0.6B v3 (ONNX on CPU). 30x faster than Whisper, 25 languages, auto-detection, OpenAI-compatible API. Use when transcribing audio files, converting speech to text, or processing voice recordings locally without cloud APIs.
carev01
Full-text search across structured Markdown documentation archives using SQLite FTS5. Use when you need to search large collections of Markdown articles that are separated by "---" delimiters and contain source URLs (marked with "*Source:" pattern). Provides fast BM25-ranked search with automatic source URL extraction for citations. Ideal for research, documentation lookups, and knowledge base exploration. Requires indexing documentation first with `docs.py index`.