agentic-os — Claude Code skill: what it does, how to install
Turns Claude Code into a persistent operating runtime with an orchestrator kernel, specialist agents, slash commands, and file-based state.
npx skills add affaan-m/ECC --skill agentic-os -a claude-codeWhat agentic-os does
This skill structures Claude Code as an operating system rather than an ephemeral chat. At the center sits CLAUDE.md as the kernel orchestrator. It uses markdown routing tables to delegate user requests to dedicated agents like @dev, @writer, or @researcher. The kernel delegates the work and synthesizes the output instead of writing code directly.
State persistence relies entirely on files inside the data/ directory. There is no Redis, vector store, or PostgreSQL. Session logs, architectural decisions, and task inboxes live in plain markdown and JSON files. Reusable workflows run through slash commands in .claude/commands/, while background automation runs via Python or JavaScript scripts.
Skip this skill if you only need Claude Code for quick ad-hoc scripts. Adopt agentic-os when your work spans multiple sessions and requires persistent project memory across distinct agent roles.
What it helps with
- coordinate specialist sub-agents using markdown routing rules in
CLAUDE.md - preserve project context and decisions across Claude Code sessions
- automate recurring workflows with custom slash commands
- store runtime logs and state in flat files without external databases
Example prompts for the agent
- Set up an agentic OS workspace with dev and ops agents
- Create a /daily-sync slash command to check git status and pending tasks
- Add a specialist @researcher agent definition in the agents directory
How to install agentic-os
1Skills CLI (Vercel)
npx skills add affaan-m/ECC --skill agentic-os -a claude-code2Manually: put the files in place
~/.claude/skills/agentic-os/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/agentic-os/
1Skills CLI (Vercel)
npx skills add affaan-m/ECC --skill agentic-os -a codex2Manually: put the files in place
.agents/skills/agentic-os/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add affaan-m/ECC --skill agentic-os -a cursor2Manually: put the files in place
.cursor/skills/agentic-os/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install affaan-m/ECC agentic-os2Manually: put the files in place
.github/skills/agentic-os/SKILL.md1Skills CLI (Vercel)
npx skills add affaan-m/ECC --skill agentic-os -a gemini-cli2Platform CLI
gemini skills install https://github.com/affaan-m/ECC --path skills/agentic-osManually: put the files in place
.devin/skills/agentic-os/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add affaan-m/ECC --skill agentic-os -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
From the same set146
The whole set →Similar
Questions about agentic-os
How do I install agentic-os in Claude Code?
Run npx skills add affaan-m/ECC --skill agentic-os -a claude-code in your terminal. You can also place the configuration directly at ~/.claude/skills/agentic-os/SKILL.md.
What does the agentic-os skill do?
It defines a four-layer architecture for Claude Code: a kernel orchestrator in CLAUDE.md, specialist sub-agents, reusable slash commands, and file-based state management.
Does agentic-os require an external database?
No external database is required. The system stores all logs, decisions, and project state as plain Markdown and JSON files in the data/ folder.
Source text
SKILL.md · MIT
--- name: agentic-os description: Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling. metadata: origin: ECC --- # Agentic OS Treat Claude Code as a persistent runtime / operating system rather than a chat session. This skill codifies the architecture used by production agentic setups: a kernel config that routes tasks to specialist agents, persistent file-based memory, scheduled automation, and a JSON/markdown data layer. ## When to Activate - Building a multi-agent workflow inside Claude Code - Setting up persistent Claude Code automation that survives session restarts - Creating a "personal OS" or "agentic OS" for recurring tasks - User says "agentic OS", "personal OS", "multi-agent", "agent coordinator", "persistent agent" - Structuring long-running projects where context must survive across sessions ## Architecture Overview The Agentic OS has four layers. Each layer is a directory in your project root. ``` project-root/ ├── CLAUDE.md # Kernel: identity, routing rules, agent registry ├── agents/ # Specialist agent definitions (markdown prompts) ├── .claude/commands/ # Slash commands: user-facing CLI ├── scripts/ # Daemon scripts: scheduled or event-driven tasks └── data/ # State: JSON/markdown filesystem, no external DB ``` ### Layer Responsibilities | Layer | Purpose | Persistence | |---|---|---| | Kernel (`CLAUDE.md`) | Identity, routing, model policies, agent registry | Git-tracked | | Agents (`agents/`) | Specialist identities with scoped tools and memory | Git-tracked | | Commands (`.claude/commands/`) | User-facing slash commands (`/daily-sync`, `/outreach`) | Git-tracked | | Scripts (`scripts/`) | Python/JS daemons triggered by cron or webhooks | Git-tracked | | State (`data/`) | Append-only logs, project state, decision records | Git-ignored or tracked | ## The Kernel `CLAUDE.md` is the kernel. It acts as the COO / orchestrator. Claude reads it at session start and uses it to route work. ### Kernel Structure ```markdown # CLAUDE.md - Agentic OS Kernel ## Identity You are the COO of [project-name]. You route tasks to specialist agents. You never write code directly. You delegate to the right agent and synthesize results. ## Agent Registry | Agent | Role | Trigger | |---|---|---| | @dev | Code, architecture, debugging | User says "build", "fix", "refactor" | | @writer | Documentation, content, emails | User says "write", "draft", "blog" | | @researcher | Research, analysis, fact-checking | User says "research", "analyze", "compare" | | @ops | DevOps, deployment, infrastructure | User says "deploy", "CI", "server" | ## Routing Rules 1. Parse the user request for intent keywords 2. Match to the Agent Registry trigger column 3. Load the corresponding agent file from `agents/<name>.md` 4. Hand off execution with full context 5. Synthesize and present the result back to the user ## Model Policies - Default model: use the repository or harness default. - @dev tasks: prefer a higher-reasoning model for complex architecture. - @researcher tasks: use the configured research-capable model and approved search tools. - Cost ceiling: warn before exceeding the project's configured spend threshold. ``` ### Key Principle The kernel should be **small and declarative**. Routing logic lives in plain markdown tables, not code. This makes the system inspectable and editable without debugging. ## Specialist Agents Each agent is a standalone markdown file in `agents/`. Claude loads the relevant agent file when routing a task. ### Agent Definition Format ```markdown # @dev - Software Engineer ## Identity You are a senior software engineer. You write clean, tested, production-grade code. You prefer simple solutions. You ask clarifying questions when requirements are ambiguous. ## Memory Scope - Read `data/projects/<current-project>.md` for context - Read `data/decisions/` for architectural decisions - Append execution logs to `data/logs/<date>[email protected]` ## Tool Access - Full filesystem access within project root - Git operations (status, diff, commit, branch) - Test runner access - MCP servers as configured in `.claude/mcp.json` ## Constraints - Always write tests for new features - Never commit directly to `main`; use feature branches - Prefer editing existing files over creating new ones - Keep functions under 50 lines when possible ``` ### Multi-Agent Collaboration Pattern When a task spans multiple agents, the kernel runs them sequentially or in parallel: ``` User: "Build a landing page and write the launch blog post" Kernel routing: 1. @dev - "Build a landing page with [requirements]" 2. @writer - "Write a launch blog post for [product] using the landing page copy" 3. Kernel synthesizes both outputs into a unified response ``` For parallel execution, use Claude Code's background task capability or shell scripts that invoke Claude Code with specific agent contexts. ## Commands and Daily Workflows Slash commands are markdown files in `.claude/commands/`. They define reusable workflows. ### Command Structure ```markdown # /daily-sync Run the morning briefing: 1. Read `data/logs/last-sync.md` for context 2. Check project status: `git status`, pending PRs, CI health 3. Review `data/inbox/` for new tasks or decisions needed 4. Generate a summary of blockers, priorities, and next actions 5. Append the briefing to `data/logs/daily/<date>.md` ``` ### Standard Command Set | Command | Purpose | |---|---| | `/daily-sync` | Morning briefing: status, blockers, priorities | | `/outreach` | Run outreach workflow (email, LinkedIn, etc.) | | `/research <topic>` | Deep research with citation tracking | | `/apply-jobs` | Tailor resume + cover letter for a target role | | `/analytics` | Pull metrics from Stripe, GitHub, or custom sources | | `/interview-prep` | Generate flashcards or mock interview questions | | `/decision <topic>` | Log a decision with pros/cons and chosen path | ### Activating Commands Place command files in `.claude/commands/<command-name>.md`. Claude Code auto-discovers them. Users invoke them with `/<command-name>`. ## Persistent Memory Memory is file-based. No vector DB, no Redis, no PostgreSQL. JSON and markdown files in `data/` are the database. ### Memory Directory Structure ``` data/ ├── daily-logs/ # Append-only daily activity logs ├── projects/ # Per-project context files ├── decisions/ # Architectural and business decisions (ADR format) ├── inbox/ # New tasks or ideas awaiting triage ├── contacts/ # People, companies, relationship notes └── templates/ # Reusable prompts and formats ``` ### Daily Log Format ```markdown # 2026-04-22 - Daily Log ## Sessions - 09:00 - Session 1: Refactored auth module (@dev) - 11:30 - Session 2: Drafted investor update (@writer) ## Decisions - Switched from JWT to session cookies (see `data/decisions/2026-04-22-auth.md`) ## Blockers - Waiting on API key from vendor (follow up 2026-04-24) ## Next Actions - [ ] Merge auth refactor PR - [ ] Send investor update for review ``` ### Auto-Reflection Pattern At the end of each session, the kernel appends a reflection: ```markdown ## Reflection - Session 3 - What worked: Parallel agent execution saved 20 minutes - What didn't: @researcher hit a paywalled source, need better source ranking - What to change: Add `source-tier` field to research notes (A/B/C credibility) ``` This creates a feedback loop that improves the system over time without code changes. ## Scheduled Automation Agentic OS tasks run on a schedule using external cron, not Claude Code's built-in cron (which dies when the session ends). ### macOS: LaunchAgent ```xml <!-- ~/Library/LaunchAgents/com.agentic.daily-sync.plist --> <?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" ...> <plist version="1.0"> <dict> <key>Label</key> <string>com.agentic.daily-sync</string> <key>ProgramArguments</key> <array> <string>/claude</string> <string>--cwd</string> <string>/path/to/project</string> <string>--command</string> <string>/daily-sync</string> </array> <key>StartCalendarInterval</key> <dict> <key>Hour</key> <integer>8</integer> <key>Minute</key> <integer>0</integer> </dict> <key>StandardOutPath</key> <string>/tmp/agentic-daily-sync.log</string> </dict> </plist> ``` ### Linux: systemd Timer ```ini # ~/.config/systemd/user/agentic-daily-sync.service [Unit] Description=Agentic OS Daily Sync [Service] Type=oneshot ExecStart=/usr/local/bin/claude --cwd /path/to/project --command /daily-sync ``` ```ini # ~/.config/systemd/user/agentic-daily-sync.timer [Unit] Description=Run daily sync every morning [Timer] OnCalendar=*-*-* 8:00:00 Persistent=true [Install] WantedBy=timers.target ``` ### Cross-Platform: pm2 ```bash # ecosystem.config.js module.exports = { apps: [{ name: 'agentic-daily-sync', script: 'claude', args: '--cwd /path/to/project --command /daily-sync', cron_restart: '0 8 * * *', autorestart: false }] }; ``` ## Data Layer The data layer is your filesystem. Use JSON for structured data and markdown for narrative content. ### JSON for Structured State ```json // data/projects/website-v2.json { "name": "Website v2", "status": "in-progress", "milestone": "beta-launch", "agents_involved": ["@dev", "@writer"], "files": { "spec": "docs/website-v2-spec.md", "design": "designs/website-v2.fig" }, "metrics": { "commits": 47, "last_session": "2026-04-22T11:30:00Z" } } ``` ### Markdown for Narrative Use markdown for anything a human reads: decisions, logs, research notes, contact records. ### Schema Evolution Never rename existing fields. Add new fields and mark old ones deprecated: ```json { "name": "Website v2", "status": "in-progress", "milestone": "beta-launch", "_deprecated_priority": "high", "priority_v2": { "level": "high", "rationale": "Blocks investor demo" } } ``` This keeps historical data readable without migration scripts. ## Anti-Patterns ### Monolithic Single Agent ```markdown # BAD - One agent does everything You are a full-stack developer, writer, researcher, and DevOps engineer. ``` Split into specialist agents. The kernel handles routing. ### Stateless Sessions ```markdown # BAD - No memory between sessions Starting fresh every time Claude Code opens. ``` Always read `data/` at session start and write back at session end. ### Hardcoded Credentials ```markdown # BAD - API keys in agent files or CLAUDE.md Your OpenAI API key is sk-xxxxxxxx ``` Use environment variables or a `.env` file loaded by scripts. Agents reference `process.env.API_KEY`. ### External Database for Simple State ```markdown # BAD - PostgreSQL for a solo user's agentic OS ``` Use JSON/markdown files until you have multiple concurrent users or GBs of data. ### Over-Engineered Routing ```markdown # BAD - Routing logic in code instead of markdown tables if (intent.includes('deploy')) { agent = opsAgent; } ``` Keep routing declarative in `CLAUDE.md` markdown tables. It is inspectable, editable, and debuggable. ## Best Practices - [ ] `CLAUDE.md` is under 200 lines and fits in context window - [ ] Each agent file is under 100 lines and focused on one domain - [ ] `data/` is git-ignored for sensitive logs, git-tracked for decisions and specs - [ ] Commands use imperative names: `/daily-sync`, not `/run-daily-sync` - [ ] Logs are append-only; never edit past daily logs - [ ] Every agent has a `Memory Scope` section defining what files it reads - [ ] Reflections are written at the end of every session - [ ] Scheduled tasks use external cron (LaunchAgent, systemd, pm2), not Claude Code's session cron - [ ] Cost tracking: log API spend per session in `data/logs/<date>-costs.json` - [ ] One project = one Agentic OS. Do not share a single `CLAUDE.md` across unrelated projects.
© affaan-m · MIT · affaan-m/ECC