/ruflo-doctor
Run health checks on the Ruflo installation and fix common issues
$ npx -y skills add ruvnet/ruflo --skill ruflo-doctor --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/ruflo-doctor
Context preview
The summary Claude sees to decide when to auto-load this skill.
Run health checks on the Ruflo installation and fix common issues
SKILL.md
ruflo-doctor.SKILL.mdname: ruflo-doctor description: Run health checks on the Ruflo installation and fix common issues argument-hint: "[--fix]" allowed-tools: Bash(npx *)
Run `npx @claude-flow/cli@latest doctor --fix` to diagnose and auto-repair common issues.
Checks: Node.js 20+, npm 9+, git, config validity, daemon status, memory database, API keys, MCP servers, disk space, TypeScript.
Targeted fixes:
- Memory: `npx @claude-flow/cli@latest memory init --force`
- Daemon: `npx @claude-flow/cli@latest daemon start`
- Config: `npx @claude-flow/cli@latest config reset`
An agent meta-harness for Claude Code and Codex. Agent = Model + Harness. The model writes; the harness gives it tools, memory, loops, sandboxes, and controls so it can actually work.
Repo: ruvnet/ruflo
Other skills on claude-flow.
- /agentdb-advanced
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
Open skill - /agentdb-learning
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
Open skill - /agentdb-memory-patterns
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
Open skill - /agentdb-optimization
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
Open skill - /agentdb-vector-search
Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
Open skill - /agentic-jujutsu
Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
Open skill

