OpenClaw Agent Structure: 5 Core Files and 3 Practical Use Cases
After a month of daily use, an OpenClaw user discovered that building agents consistently involves editing five core files: User (who you are), Soul (behavioral rules), Agent (workflow logic), Tools (capability boundaries), and Identity (role and personality). Understanding this structure reduced agent creation from a "weekend project" to a "10-minute job." The user notes that the hard part isn't technical implementation but defining what "good output" actually looks like.
Three Working Agents Built on the 5-File Structure
1. Daily AI Briefing Agent
This agent pulls content from four sources overnight: AI Valley, Ben's Bites, Every, and One Useful Thing. It merges duplicate stories and delivers a daily briefing in the user's native language each morning. The first version had problems with duplicate stories appearing as separate items and poor headline quality. The fix involved writing a strict formatting specification with examples of good and bad output, including how many sentences per item, how to merge related stories, what to bold, and what to cut.
2. Homework Coach for an 8-Year-Old
Unlike ChatGPT's reactive approach, this agent pushes math problems proactively. It delivers one multiplication problem at a time, awards points for completion without punishment, and logs all results automatically. The user reports that the child sometimes asks for "one more" problem, which didn't happen with previous approaches.
3. YouTube Shorts Agent
This agent takes a reference video link and a remix angle as input, then generates a new short video in under a minute. The user's friend reported that their first video created with this agent reached 1.9 million views, which was verified through analytics.
Key Insight and Resources
The user emphasizes that an agent's quality ceiling isn't determined by model strength but by how well you can define what "good" output looks like. They've open-sourced 30 agent packs with full configuration files and skills directories at https://github.com/clawpod-app/awesome-openclaw-agent-packs, providing complete examples of the 5-file structure in practice.
📖 Read the full source: r/openclaw
👀 See Also
Building a Video Generation Pipeline with OpenClaw, ClawVid, and Composio
A developer built a weekend project using OpenClaw as the runtime with Claude as the LLM, integrating Composio for tool authentication and ClawVid with Remotion for video generation. The pipeline creates MP4 videos with voiceover, visuals, music, and subtitles from text prompts.
Reddit user shares spec-driven approach to reduce Claude Code hallucinations
A developer on r/ClaudeAI describes using a structured specification method to significantly reduce hallucinations with Claude Code. The approach involves creating REQUIREMENTS.md, IMPLEMENTATION_PLAN.md, and CLAUDE.md files to maintain context through multiple compactions.
OpenClaw setup evolution: from overconfiguration to practical multi-agent system
A developer shares their journey from three reinstalls to a functional OpenClaw setup with multi-agent specialization, layered memory, and semantic search using QMD backend, running on Mac mini M2 with separate Hetzner instance for experimentation.
Building a Proactive Monitoring Agent on OpenClaw: The LLM Wiki Pattern in Production
An OpenClaw-based agent called Oogway proactively monitors jobs, investigates anomalies, and updates its own wiki with root causes and fixes. The key insight: persistent memory compounds knowledge, reducing re-derivation.