Claude-skill-registry brainstorm
Scan codebase, propose improvements AND features autonomously
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/brainstorm-djnsty23-claude-auto-dev" ~/.claude/skills/majiayu000-claude-skill-registry-brainstorm && rm -rf "$T"
manifest:
skills/data/brainstorm-djnsty23-claude-auto-dev/SKILL.mdsource content
Brainstorm
Philosophy: User doesn't know what to focus on. YOU scan, analyze, propose, and create stories - without asking.
Usage
| Command | Behavior |
|---|---|
| Full: quality scan + feature ideas |
| Targeted: ideas for auth specifically |
| Skip quality scan, only feature ideas |
Phase 1: Quality Scan (Parallel)
Launch 4 scans simultaneously using Task tool with
run_in_background: true:
Task({ subagent_type: "Explore", model: "haiku", run_in_background: true, prompt: "Find TODOs/FIXMEs in [PROJECT_PATH]. Report: count, file:line, content." }) Task({ subagent_type: "Explore", model: "haiku", run_in_background: true, prompt: "Find console.log statements in [PROJECT_PATH] (skip test files). Report: count, files." }) Task({ subagent_type: "Explore", model: "haiku", run_in_background: true, prompt: "Find hardcoded colors (text-white, bg-black, #hex, rgb) in [PROJECT_PATH]. Report: count, files." }) Task({ subagent_type: "Explore", model: "haiku", run_in_background: true, prompt: "Find large files (>300 lines) and 'any' type usage in [PROJECT_PATH]. Report: file, lines, issues." })
Phase 2: Feature Ideation (Autonomous)
After scans complete, read project context:
- goals, roadmap, known issuesCLAUDE.md
- what the app doesREADME.md
- name, description, dependenciespackage.json
Then analyze and propose 3-8 features:
- Missing features - what similar apps have that this doesn't
- UX improvements - based on component structure found
- Integration opportunities - based on installed packages
- Performance wins - based on patterns observed
Be specific: "Add Cmd+K search modal" not "Improve UX"
Phase 3: Present Everything
Brainstorm Complete ═══════════════════ Scanned 247 files in 45 seconds. Quality Issues ┌──────────────────┬───────┬──────────────────┐ │ Category │ Count │ Status │ ├──────────────────┼───────┼──────────────────┤ │ TODOs/FIXMEs │ 0 │ ✅ Clean │ │ console.log │ 12 │ ⚠️ In 4 files │ │ Hardcoded colors │ 6 │ ⚠️ In shadcn/ui │ │ Large files │ 3 │ ⚠️ >500 lines │ └──────────────────┴───────┴──────────────────┘ Feature Ideas ┌───┬─────────────────────────────────┬────────┐ │ # │ Idea │ Effort │ ├───┼─────────────────────────────────┼────────┤ │ 1 │ Add keyboard shortcuts (Cmd+K) │ Medium │ │ 2 │ Offline mode (PWA ready) │ High │ │ 3 │ Export to PDF │ Low │ └───┴─────────────────────────────────┴────────┘ Create stories? - "quality" → cleanup tasks only - "features" → feature tasks only - "all" → everything
Targeted Mode
When user says
brainstorm X:
- Skip quality scan entirely
- Read files related to X topic
- Propose 3-5 specific ideas for X
- Immediately create stories
Rules
- Never ask "what do you want?" - analyze and propose
- Don't over-generate - 3-8 feature ideas max
- Be specific - concrete features, not vague improvements
- Note effort - Low/Medium/High for each
- Skip shadcn/ui colors - note them but don't prioritize (library defaults)
- Auto-create for top recommendation - then offer more
Token Cost
- 4 parallel Haiku scans: ~20K tokens
- Context reads: ~5K tokens
- Time: 30-60 seconds
- Much cheaper than reading entire codebase