Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add unrealandychan/clean-code-skill --skill agentic-osgit clone --depth 1 https://github.com/unrealandychan/clean-code-skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/unrealandychan/clean-code-skill/agentic-os)<a href="https://agentmods.dev/skills/unrealandychan/clean-code-skill/agentic-os"><img src="https://agentmods.dev/badge/skills/unrealandychan/clean-code-skill/agentic-os/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/unrealandychan/clean-code-skill/agentic-os"><img src="https://agentmods.dev/badge/skills/unrealandychan/clean-code-skill/agentic-os.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00059 | $0.02984 |
| Opus 5.5 | $0.00024 | $0.01194 |
| Sonnet 5.5 | $0.00012 | $0.00597 |
| Haiku 4.5 | $0.00006 | $0.00298 |
Grade A, and why
agentic-os scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
95% identical to agentic-os — 28 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 389 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
# 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.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 389 lines · 59 tokens per session scan A e1d120735365
agentic-os is a skill published in the GitHub repository unrealandychan/clean-code-skill (12 stars, last pushed 1mo ago), licensed MIT. It adds 59 tokens to every session and 2,984 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to agentic-os, differing in 28 lines, and is treated as a copy.
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