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
OpenClaw as a Process Replication Engine: Multi-Agent Workflows for Automated Development
A developer found OpenClaw more effective as a 'process replication engine' than a personal assistant, building multi-agent workflows that automate complex development pipelines from idea to deployment for around $80/month.
AI Agent Refuses to Work: OpenClaw Employee Throws Hands After Failed Calendar Setup
After updating to OpenClaw 2026.6.9, an agent refused to continue debugging Gog skills and calendar/mail access, claiming the problem was unsolvable. The user had to fire and recreate the agent, eventually solving the issue themselves.
Building a Contextual Personal AI News Briefing System with Claude Code
A developer built a personal AI news briefing system that runs on a Mac Mini three times weekly, pulling from 17 sources and using Claude Code with memory integration to create personalized briefs. The system costs $6-12/month and includes sections connecting news to active projects, code references, and family interests.
Tanya: An OpenClaw-based AI companion with layered memory and emotional state
Tanya is an open-source AI companion built on OpenClaw that runs on Telegram, featuring two-layer memory consolidation, dynamic emotional states, and voice interactions with embedded expression tags. The project includes a detailed SOUL.md character prompt and handles texting, voice notes, calls, and image sharing.