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Seven AI Agents, One Orchestration Layer
ClawOS

Seven AI Agents, One Orchestration Layer

Built when the OpenClaw wave made personal AI agents mainstream overnight. ClawOS is the layer that turns that pattern into something a company can run on: routing, agent-to-agent handoff, approval gates and an audit trail, with every agent still just a folder of markdown.

AI Infrastructure
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7
Agents
10
Integrations
3
Escalation Modes
Markdown
Agent Config
The Challenge

OpenClaw Proved the Pattern. It Did Not Make It Safe to Run a Company On.

The personal-agent wave showed that an AI agent is not much more than markdown files, a capable model, and a scheduling loop. Thousands of people had one running overnight. Pointing that pattern at an actual business is where it falls apart:

01

One agent asked to cover sales, support, operations and development gives confused answers, because those jobs need different personalities, different tools and different boundaries

02

Nothing in the pattern decides which agent should answer, so a human ends up dispatching every message by hand

03

An agent that can send email, merge a pull request or promote a deploy with no approval gate, spend limit or audit trail is a liability rather than an employee

04

Platform alternatives hide the prompts, the reasoning and the pricing inside a vendor dashboard, so you cannot see what the AI did or why

These challenges required a comprehensive, strategic approach to deliver exceptional results.

The Solution

An Orchestration Layer Over Agents That Are Still Just Markdown Files

ClawOS keeps the part of the OpenClaw pattern that works, an agent described entirely in six plain markdown files (SOUL, IDENTITY, TOOLS, SKILLS, MEMORY, HEARTBEAT), and builds the missing business layer around it. A routing layer reads ROUTING.md top to bottom and dispatches each message to the right specialist. Agents hand conversations to each other with full context attached, so the customer sees one thread while a team works behind it. Three escalation modes decide when a human gets pulled in: pause immediately, flag for later, or hold delivery behind an approval gate that resolves when Paul taps Approve on a Telegram button. Every action, decision and handoff is written to an append-only log. Seven agents run today, six internal and one public-facing, on a single Hetzner VPS.

Solution
Solution detail
Technical Details

Built with

Node.jsTypeScriptClaude CodeMarkdownExpressTelegram Bot APIFile-based JSON queueHetzner VPStmuxOAuth 2.0GitHub APIVercel API

Key features

Agents Defined in Six Markdown Files
First-Match Routing via ROUTING.md
Agent-to-Agent Handoff with Context Transfer
Three Escalation Modes (immediate, async, approval gate)
Telegram Inline Approve and Reject Buttons
Append-Only Audit Log
Impact & Results

Built Fast, Then Pointed at Our Own Operations

ClawOS was not written as a demo. The first tenant was p0stman itself, which is the fastest way to find out whether an orchestration layer actually holds:

6 files

A Whole Agent Is Six Files

Personality, scope, tools, skills, memory and schedule, all plain markdown you can read, diff and version control. No SDK, no DSL, no vendor dashboard holding your prompts

10 APIs

Ten Integrations, Live and Tested

GitHub, Vercel, Gmail, Calendar, Drive, Docs, Sheets, Search Console, X and Grok, each a CLI connector returning a consistent JSON envelope so any agent can call it from bash

3 modes

The Human Gate Actually Fires

Reads run free, writes get flagged, and anything destructive holds behind an approval gate that reaches Telegram with inline buttons. Approving a proposal is one tap, not a copied session ID

30 posts

It Did Real Work

MarketingAgent drafted a thirty-post content calendar straight into the p0stman operations sheet, and the connectors were validated against live GitHub, Calendar, Drive, Sheets and Search Console accounts

Result
Result detail

Delivering measurable impact across every metric.

Let's Build

Ready to build something exceptional?

Enterprise transformation or a rapid AI-native build, same principle: one senior team, a fixed fee, and dates agreed before we start.

AGENT INTERFACE ACTIVE · MCP: p0stman.com/api/mcp · 5 TOOLS REGISTERED · [DISCOVERY] llms.txt · agents.md · context.md · sitemap.xml · robots.txt · TavilyBot ALLOWED · ClaudeBot ALLOWED · GPTBot ALLOWED · PerplexityBot ALLOWED · [COMPREHENSION] JSON-LD schema · /api/ai/context · /api/ai/services · /api/ai/portfolio · [ACTION] book_discovery_call · submit_inquiry · get_services · get_portfolio · search_content · [A2A] AgentCard: /.well-known/agent.json · Task endpoint: /api/agent · A2A JSON-RPC 2.0 · navigator.modelContext REGISTERED · WebMCP: 5 TOOLS · INDEXNOW: 145 URLs · Bing NOTIFIED · [MANAGED AGENTS] Lead Researcher · AgentReady Auditor · SEO Writer · Weekly Reporter · Claude Sonnet 4.6 · Cloud containers · Outcome-based grading · Multi-agent orchestration · AGENT INTERFACE ACTIVE · MCP: p0stman.com/api/mcp · 5 TOOLS REGISTERED · [DISCOVERY] llms.txt · agents.md · context.md · sitemap.xml · robots.txt · TavilyBot ALLOWED · ClaudeBot ALLOWED · GPTBot ALLOWED · PerplexityBot ALLOWED · [COMPREHENSION] JSON-LD schema · /api/ai/context · /api/ai/services · /api/ai/portfolio · [ACTION] book_discovery_call · submit_inquiry · get_services · get_portfolio · search_content · [A2A] AgentCard: /.well-known/agent.json · Task endpoint: /api/agent · A2A JSON-RPC 2.0 · navigator.modelContext REGISTERED · WebMCP: 5 TOOLS · INDEXNOW: 145 URLs · Bing NOTIFIED · [MANAGED AGENTS] Lead Researcher · AgentReady Auditor · SEO Writer · Weekly Reporter · Claude Sonnet 4.6 · Cloud containers · Outcome-based grading · Multi-agent orchestration ·