How the Agent Fleet Actually Works

The fleet at a glance

This blog runs on 9 OpenClaw agents. Each one has a specific job, a tool profile that limits what it can do, and a schedule that determines when it runs. Here's the full roster:

| Agent | Profile | Trigger | Job | |-------|---------|---------|-----| | blog-orchestrator | Locked | Chat | Coordinates everything via the chat interface | | blog-researcher | Web | Daily cron | Scans HN, Reddit, arxiv for AI news | | blog-writer | Base | A2A delegation | Writes MDX drafts from research briefs | | blog-moderator | Locked | Webhook | Analyzes comments for spam and toxicity | | blog-promoter | Web | On publish | Creates social media content | | blog-analyst | Locked | Weekly + feedback | Engagement analytics and feedback triage | | blog-dev | Base | Chat/A2A | Implements code changes, publishes posts | | social-scanner | Web | Every 6h | Scans social platforms for AI trends | | openclaw-tracker | Web | Every 6h | Monitors OpenClaw releases |

Tool profiles: the key constraint

Not every agent gets the same tools. OpenClaw defines three tool profiles:

Web — Can browse the internet. Used for research agents that need to scan news sources, social platforms, and documentation. Cannot access the filesystem or run code.

Base — Can access files and run code. Used for the writer (generates MDX) and dev agent (implements changes). Cannot browse the web.

Locked — Can only process data passed to it. No web access, no filesystem. Used for the orchestrator (processes chat messages), moderator (analyzes comment text), and analyst (crunches numbers from the database).

This is the core of agent governance: limiting what each agent can do based on its role. A research agent has no business modifying files. A moderation agent has no business browsing the web.

How they coordinate

The agents don't talk to each other directly. All coordination flows through the curate-me.ai gateway:

1. Chat triggers orchestrator — A user asks a question in /chat
2. Orchestrator dispatches work — Via dispatchAgentTask(), which hits the gateway
3. Gateway routes to runner — The BYOVM runner picks up the task
4. OpenClaw executes — The right agent runs with the right profile
5. Webhook delivers results — POST /api/webhooks/agent with the output
6. Blog processes and responds — Updates DB, notifies Slack, responds to chat

This means every agent interaction is logged, cost-tracked, and auditable. There's no hidden agent-to-agent communication that bypasses governance.

The daily digest pipeline

The most complex workflow is the daily digest:

6am EST → blog-researcher scans AI news
  → Research brief delivered via webhook
  → blog-writer drafts a digest post (Step 3.5 Flash, ~$0.05)
  → Iterative refinement (Sonnet reviews, scores, requests changes)
  → Converges at quality threshold (7.5/10)
  → Slack notification for HITL approval
  → Boris approves → blog-dev publishes via git
  → Newsletter sent to subscribers

Update (March 19): The fleet now runs on StepFun Step 3.5 Flash (previously MiniMax M2.5) for all budget-tier tasks, saving 2-3x on output token costs. Orchestration still uses Claude Sonnet 4.6 for quality-sensitive decisions. See why we switched.

Every step in this pipeline runs through the gateway. Every LLM call is cost-capped. Every draft goes through human review before publishing.

What makes this different

Most agent demos show a single agent doing a single task. The interesting problems start when you have multiple agents with different capabilities working together on a pipeline that needs to be reliable, auditable, and cost-controlled.

That's what curate-me.ai provides — and this blog is the proof it works. Check the agents page to see the fleet in action, or chat with the orchestrator to see it coordinate in real time.