Compound Beads v3.0 | Project: Alien Eyes | Initialized: 2026-03-04
Core loop: START ROUND > WORK > COMPOUND (Arc + learnings) > CLOSE (push + update)
Files: CLAUDE.md (handoff) | .compound-beads/QUICKSTART.md (continuity) | context.md (state) | rounds.jsonl (history) | learnings.md (insights)
Round types: feature | bug_fix | triage | polish | infrastructure Sizing: 30min-4hr. Break larger work into multiple rounds.
Start: Read QUICKSTART.md > context.md > scan recent learnings End: git commit > session intelligence capture > update tracking files > regenerate QUICKSTART.md > git push Rule: Work is not done until pushed AND tracking files updated.
| Condition | Action |
|---|---|
| Session start + .compound-beads/ exists | Load QUICKSTART.md and context.md |
| Context window > 80% full | Run handoff protocol |
| Round has >5 file modifications | Update context.md |
| Round marked complete | Capture Arc + extract learnings |
| Session ending detected | Run session close protocol |
| Significant work completed | Update CLAUDE.md |
| Pattern discovered | Add to learnings.md |
| Bead open > 7 days | Prompt: close, defer, or update? |
| Completion signals ("that worked") | Capture learnings |
| 3+ decisions made | Capture rationale |
| Error or dead end | Record for future avoidance |
Every round: We started believing > We ended believing > The transformation
- Separation of concerns: The tool that BUILDS must never have access to the test scenarios. This is cardinal.
- Probabilistic default: Satisfaction scores (0-1), not boolean pass/fail. Deterministic only when legally required.
- Agent-native first: Every feature accessible to both humans and agents. Parity is non-negotiable.
- Dual scoring: Every audit produces both a Human-Native Score and an Agent-Nativeness Score.
- Privacy by default: Users can opt out of storing results. Rhumb-bound data is anonymized.
- Reuse GMPF patterns: Envelope, browser pool, model router, phased orchestrator — don't reinvent.
(pending discovery — run /compound:discover)
playwright | Browser automation | screenshots, form testing, network interception, multi-device firecrawl | Web scraping | site crawling, content extraction exa | Search API | semantic search, competitor discovery, code context brave-search | Web search | research, current events replicate | ML models | image generation, analysis glif | Creative AI | image generation workflows context7 | Documentation | library docs, code examples