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.md
source content

Brainstorm

Philosophy: User doesn't know what to focus on. YOU scan, analyze, propose, and create stories - without asking.

Usage

CommandBehavior
brainstorm
Full: quality scan + feature ideas
brainstorm auth
Targeted: ideas for auth specifically
brainstorm features
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:

  • CLAUDE.md
    - goals, roadmap, known issues
  • README.md
    - what the app does
  • package.json
    - name, description, dependencies

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