skills/ship-faster/skills/cloudflare/SKILL.md
Infrastructure operations for Cloudflare: Workers, KV, R2, D1, Hyperdrive, observability, builds, audit logs. Triggers: worker/KV/R2/D1/logs/build/deploy/audit. Three permission tiers: Diagnose (read-only), Change (write requires confirmation), Super Admin (isolated environment). Write operations follow read-first, confirm, execute, verify pattern. MCP is optional — works with Wrangler CLI/Dashboard too.
npx skillsauth add enuno/claude-command-and-control cloudflareInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Manage Cloudflare services: Workers, KV, R2, D1, Hyperdrive, Observability, Builds, and Audit Logs.
MCP is optional. This skill works with MCP (auto), Wrangler CLI, or Dashboard. See BACKENDS.md for execution options.
| Tier | Purpose | Scope | Risk Control | |------|---------|-------|--------------| | Diagnose | Read-only/query/troubleshoot | Observability, Builds, Audit | Default entry, no writes | | Change | Create/modify/delete resources | KV, R2, D1, Hyperdrive | Requires confirmation + verification | | Super Admin | Highest privileges | All + Container Sandbox | Only in isolated/test environments |
1. Plan: Read current state first (list/get)
2. Confirm: Output precise change (name/ID/impact), await user confirmation
3. Execute: create/delete/update
4. Verify: audit logs + observability confirm no new errors
| Category | What You Can Do | |----------|-----------------| | Observability | Query worker logs/metrics, discover fields, explore values | | Builds | List build history, get build details, view build logs | | Browser | Fetch page HTML, convert to markdown, take screenshots | | Audit | Pull change history by time range | | Workers | List workers, get details, view source code |
| Resource | Operations | |----------|------------| | KV | List, get, create ⚠️, update ⚠️, delete ⚠️ | | R2 | List, get, create ⚠️, delete ⚠️ | | D1 | List, get, query, create ⚠️, delete ⚠️ | | Hyperdrive | List, get, create ⚠️, edit ⚠️, delete ⚠️ |
⚠️ = Requires confirmation
Temporary container for isolated tasks (~10 min lifecycle):
1. Clarify symptoms → worker name / time range / error type
2. Query observability to pull logs/metrics
3. If build-related → get build logs
4. If page-related → take screenshot to reproduce
5. Trace changes → pull audit logs
6. Summarize: root cause + evidence + fix recommendations
1. List accounts → set active account
2. List resources (KV / R2 / D1)
3. Plan changes → present to user
4. Execute after confirmation
5. Verify: audit logs + observability shows no errors
Example:
✅ Investigation complete: worker `api-gateway` experienced 5xx spike between 18:00-18:30
Root cause: New code deployed threw TypeError when processing /v2/users
Evidence:
- Logs: 18:02 first occurrence of "Cannot read property 'id' of undefined"
- Audit: 18:00 user [email protected] deployed new version
- Metrics: error_rate jumped from 0.1% to 12%
Recommendation: Roll back to previous version, or fix /v2/users handler
When integrating into multi-step workflows:
runs/<workflow>/active/<run_id>/
├── proposal.md # Symptoms/objectives
├── context.json # Account/worker/resource/time_range
├── tasks.md # Checklist + approval gate
├── evidence/observability.md
├── evidence/audit.md
├── evidence/screenshots/
├── evidence/change-plan.md # Write operations written here first
├── evidence/report.md # Conclusion + evidence + next steps
└── logs/events.jsonl # Optional tool call summary
| Situation | Action | |-----------|--------| | Account not set | Run accounts_list → set_active_account first | | Resource doesn't exist | Verify ID/name, list available resources | | Insufficient permissions | Explain required permissions, check API token scope | | Observability query too broad | Split into smaller time ranges |
tools
MemPalace local-first AI memory system. Use when setting up persistent memory for Claude Code sessions, mining project files or conversation transcripts, querying past context, configuring MCP tools, managing the knowledge graph, or troubleshooting palace operations.
tools
LangSmith Python SDK — trace, evaluate, and monitor LLM applications. Covers @traceable decorator, trace context manager, Client API, evaluate() / aevaluate(), comparative evaluation, custom evaluators, dataset management, prompt caching, ASGI middleware, and pytest plugin.
development
LangGraph (Python) — build stateful, controllable agent graphs with checkpointing, streaming, persistence, interrupts, fault tolerance, and durable execution. Covers both Graph API (StateGraph) and Functional API (@entrypoint/@task).
development
LangGraph Graph API (Python) — build explicit DAG agent workflows with StateGraph, typed state, nodes, edges, Command routing, Send fan-out, checkpointers, interrupts, and streaming. Use when you need explicit control flow and graph topology.