- pgqueue package: Go wrapper around the SQL primitive
(enqueue, claim, heartbeat, ack, nack, janitor, listener)
- examples/agent-dispatcher: reference worker implementation
showing end-to-end flow with LISTEN/NOTIFY + heartbeats
- All 5 Go tests pass against live pool_manager DB
Reference: skills/data-stack-conventions.md
Migration: devops/migrations/2026-06-01_pgqueue_primitive.sql
- Activate / Deactivate via flox activate --detach (with graceful SIGTERM→SIGKILL)
- Non-privileged IsAlive process check with Linux /proc fallback
- Dev-mode stub when flox is missing or FLOXENV_DEV_MODE=1
- Unit and integration tests
Closes#16
Define kubeclaw as a Kubernetes operator that runs Scobleclaw AI agents
as first-class K8s workloads with CRDs, controller loops, and
security-hardened operator patterns.
Key deliverables in this commit:
- README.md — Project spec with CRD reference, architecture diagram,
security model, threat model, and quick-start guide
- docs/architecture.md — Deep architecture doc covering operator pattern,
sidecar design, API design, security architecture, and operations
- docs/development.md — Dev setup guide with prerequisites, commands,
testing, and local dev tips
Integrates with:
- scobleclaw#7 (Agent-Judge authorization layer)
- OpenClaw gateway for LLM provider management
- Standard Kubernetes operator patterns
Closes scobleclaw#8
Analyzes coach issues #24 (trust), #25 (engineering), and #26 (vault) — all
scored 5/10 for repetitive behavior patterns. Identifies common root cause:
all agents share deepseek-v4-flash:cloud model with no loop-detection
guardrails or iteration budgets.
Key findings:
- All 3 critiques are VALID — real systemic issue, not coach noise
- Root cause: single shallow model across all agents + no loop-breaker skills
- Coach uses same model to critique itself (self-referential grading)
- Three distinct failure patterns: yield loops, planning loops, cron loops
- Recommended fixes: guardrail skills, staleness detection, model tiering
Closes#9
