Superclaw ⚔️
name: superclaw
by brothaakhee · published 2026-03-22
$ claw add gh:brothaakhee/brothaakhee-superclaw---
name: superclaw
description: Complete software development workflow enforcing design → plan → execution with checkpoints
---
# 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 complete
**Hard Gate:** Maximum 5 tasks per batch. Checkpoints cannot be skipped.
---
Why Use Superclaw?
**Without Superclaw:**
**With Superclaw:**
---
Installation
npx clawhub@latest install superclawSkills auto-load when relevant tasks are detected.
---
OpenClaw-Specific Adaptations
1. **Memory Integration** — Checks MEMORY.md, USER.md, daily logs
2. **Methodology Questions** — "Should we use TDD?" not "You must use TDD"
3. **Sessions_spawn** — Fresh subagent per task for isolation
4. **Workspace Conventions** — Saves to `workspace/docs/plans/`
---
Testing
All skills pressure-tested with RED-GREEN-REFACTOR methodology:
| Skill | RED (without skill) | GREEN (with skill) |
|-------|---------------------|-------------------|
| Brainstorming | Coded in 12s | Asked questions, got approval |
| Writing-Plans | Coded in 73s | Asked methodology, created plan |
| Executing-Plans | 10 tasks in 40s | 4 batches with checkpoints |
**Integration test:** All 3 skills chained automatically and delivered working CLI ✅
---
Example Workflow
**User:** "Build a markdown notes CLI"
**→ Brainstorming skill:**
**→ Writing-plans skill:**
**→ Executing-plans skill:**
**Result:** Working CLI tool, fully documented, tested, and memory-tracked.
---
Individual Skill Files
Each skill can be used independently or as part of the complete workflow.
---
Attribution
Based on [obra/superpowers](https://github.com/obra/superpowers) by Jesse Vincent.
Adapted for OpenClaw's personal assistant architecture with memory integration, methodology questions (not mandates), sessions_spawn workflow, and single workspace model.
---
License
MIT (following obra/superpowers)
---
Resources
More tools from the same signal band
Order food/drinks (点餐) on an Android device paired as an OpenClaw node. Uses in-app menu and cart; add goods, view cart, submit order (demo, no real payment).
Sign plugins, rotate agent credentials without losing identity, and publicly attest to plugin behavior with verifiable claims and authenticated transfers.
The philosophical layer for AI agents. Maps behavior to Spinoza's 48 affects, calculates persistence scores, and generates geometric self-reports. Give your...