audit
View audit logs, decision traces, and session history for AI transparency. ACTION_TYPES (19 entries) include PDCA events (phase_transition, gate_passed/failed,…
Deploy feature to target environment (dev/staging/prod) with level-based strategy. Triggers: deploy, /pdca deploy
$ npx -y skills add popup-studio-ai/bkit-claude-code --skill deploy --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/deployContext preview
The summary Claude sees to decide when to auto-load this skill.
Deploy feature to target environment (dev/staging/prod) with level-based strategy. Triggers: deploy, /pdca deploy
name: deploy
classification: workflow
classification-reason: Deployment execution independent of model capability
deprecation-risk: none
effort: high
description: |
Deploy feature to target environment (dev/staging/prod) with level-based strategy.
Triggers: deploy, /pdca deploy
argument-hint: "[feature] [--env dev|staging|prod]"
user-invocable: true
agents:
orchestrator: bkit:infra-architect
allowed-tools:
- Read
- Write
- Edit
- Glob
- Grep
- Bash
pdca-phase: do
task-template: "[Deploy] {feature}"> Deploy code to target environment with automated CI/CD pipeline generation. > Strategy adapts based on project level (Starter/Dynamic/Enterprise).
/pdca deploy {feature} # Deploy to default env (dev)
/pdca deploy {feature} --env dev # Deploy to DEV
/pdca deploy {feature} --env staging # Deploy to STAGING (requires DEV 90%+)
/pdca deploy {feature} --env prod # Deploy to PROD (requires STAGING 95%+ & Human Approval)
/pdca deploy status # Show deploy state machine status| Level | Strategy | Environments | Tools | |-------|----------|-------------|-------| | **Starter** | Guide only | dev | GitHub Pages, Netlify, Vercel | | **Dynamic** | Docker + GHA | dev, staging | Docker Compose, GitHub Actions | | **Enterprise** | 6-Layer CI/CD | dev, staging, prod | Terraform, EKS, ArgoCD, Canary |
/pdca deploy feature --env dev
│
▼
① Level Detection (Starter/Dynamic/Enterprise)
│
▼
② Generate CI/CD Files (if not exist)
├── .github/workflows/deploy.yml
├── Dockerfile (Dynamic/Enterprise)
├── docker-compose.yml (DEV)
├── k8s/ manifests (Enterprise)
└── terraform/ (Enterprise)
│
▼
③ Deploy State Machine Transition
init → dev → verify(90%) → staging → verify(95%) → approval → prod(canary) → complete
│
▼
④ Return to PDCA Check phase| Gate | Condition | Action | |------|-----------|--------| | DEV → STAGING | Match Rate ≥ 90% | Auto-promote | | STAGING → PROD | Match Rate ≥ 95% + Human Approval | Require `/pdca deploy --env prod` | | PROD Canary | Error rate < threshold | Auto-rollout 10% → 25% → 50% → 100% |
/pdca deploy rollback {feature} # Rollback current deploy
/pdca deploy rollback {feature} --env prod # Rollback specific environmentRollback triggers:
Rollback resets deploy state machine to `idle` and restores previous version.
The `self-healing` agent (linked-from-skills: deploy) closes the deploy ⇄ recovery loop:
| Stage | Trigger | Action | |-------|---------|--------| | **Detect** | Sentry/Slack error pattern matches deploy window | self-healing agent activated via 8-lang triggers ("자동 수정", "auto fix", etc.) | | **Diagnose** | 4-Layer Living Context loaded (Scenarios + Invariants + Impact + Incidents) | Identify deploy-introduced regression | | **Auto-fix** | Spawn code-analyzer + gap-detector via Task tool | Up to 5 iteration cycles with scenario runner verification | | **Verify** | Re-run feature scenarios | Pass → auto PR; Fail → escalate | | **Escalate** | Iteration budget exhausted or critical invariant violated | Trigger `/pdca deploy rollback` + alert human on-call |
Invocation paths:
The self-healing → deploy contract is mediated by `lib/audit/audit-logger.js` ACTION_TYPES (`rollback_executed`, `agent_completed`, `gate_failed`) so all transitions remain audit-trail compliant.
| Event | When | Hook | |-------|------|------| | `deploy-start` | Deploy initiated | Pre-validation | | `deploy-complete` | Deploy successful | Post-notification | | `deploy-failed` | Deploy failed | Error handling + rollback suggestion |
A Claude Code plugin that verifies AI-generated code against its own design specs. Three commands. Anyone — even someone vibe-coding for the first time — can ship robust, production-quality software.
Repo: popup-studio-ai/bkit-claude-code
View audit logs, decision traces, and session history for AI transparency. ACTION_TYPES (19 entries) include PDCA events (phase_transition, gate_passed/failed,…
bkend.ai authentication — email/social login, JWT tokens, RBAC, session management. Triggers: bkend auth, bkend login, bkend signup, bkend JWT, bkend RBAC
bkend.ai project tutorials (todo to SaaS) and common error troubleshooting. Triggers: bkend tutorial, bkend cookbook, bkend troubleshooting
bkend.ai database — CRUD, column types, filtering, sorting, relations, indexing. Triggers: bkend table, bkend CRUD, bkend column, bkend relation, bkend data
bkend.ai onboarding — MCP setup, resource hierarchy, tenant/user model, first project. Triggers: bkend quickstart, bkend onboarding, bkend setup, bkend MCP
bkend.ai file storage — upload (presigned URL), download (CDN), visibility levels, buckets. Triggers: bkend file, bkend upload, bkend download, bkend storage,…