openclaw-workspace

Summary

A modular OpenClaw AI workspace for personal productivity, automation, and strategic job/content management. It provides structured documentation and code supporting the use of multi-agent systems, memory management, and mission/task tracking. Includes a robust knowledge base, agent coordination guidelines, environment setup instructions, and an integrated task board for operational efficiency.

Included Assets

• AGENTS.md: Documentation of agent roles, triggers, model assignments, and coordination protocols.
• MEMORY.md: Guidelines and workflows for content and task memory, including rules for CV creation and content pipelines.
• SOUL.md: Defines workspace values, operating principles, and boundaries for agent conduct.
• TOOLS.md: Technical configuration and environment setup for AI models and workflows.
• knowledge-base/:
  • README.md: Instructions for using the SQLite-based knowledge base system, with ingestion/search commands.
• mission-control/:
  • README.md: Setup and usage for the Next.js/Convex-powered task board web app.
  • package.json: Dependencies for the task board frontend.
• skills/brave-search/node_modules/: JS utility libraries for DOM/CSS/color handling, included as part of the workspace's skill extensions.

How to Use

Agents, Memory, and Tools

• Start by reading AGENTS.md and SOUL.md to understand the purpose and operating principles of each agent and the overall workspace ethos.
• All tasks must be logged in Mission Control before work starts. See API instructions in AGENTS.md.
• Memory:
  • Review MEMORY.md for structured workflows (job applications, content pipeline).
  • For resumes and job content, follow detailed filename and approval guidelines.
• Technical Configuration:
  • Use TOOLS.md to select/approve AI models for each task type.
  • Follow model selection rules and environment setup guidance for optimal performance.

Knowledge Base

1. Ingest Sources:
   • python3 ingest.py <url> auto-detects content type (article, video, pdf, tweet).
2. Search:
   • python3 ingest.py search <query> to retrive content.
3. List Sources:
   • python3 ingest.py list to view recently added knowledge assets.

Mission Control Task Board

1. Setup:
   • Enter mission-control/ and install dependencies:
     npm install
   • Set your Convex project ID in .env.local.
2. Run locally:
   npm run dev and visit http://localhost:3000.
3. Deploy (optional):
   Use Vercel CLI for easy deployment.

Notes

• The workspace is best used with Node.js 18+ and Python 3+.
• Mission Control (the Next.js UI) requires a free Convex project for real-time collaboration and data storage.
• Agent and memory documentation enforce clear task flows and role separation, minimizing confusion in multi-agent scenarios.
• The workspace is modular; assets, agents, and workflows can be adapted to custom use cases.
• For third-party Node libraries in skills/brave-search/node_modules, refer to their upstream documentation for usage details. They are included as dependencies but are not directly documented in the core workspace README.
• Always review and follow non-negotiable task logging and proactive memory checklists for consistent operation.