openclaw-mongoz
Summary
This workspace provides configuration, coordination scripts, and agent setup for orchestrating OpenClaw environments. It includes guides, active project memory, agent persona definitions, automation tools, and both trading and research skill integrations. The setup emphasizes secure workflows, agent delegation, rigorous audit trails, and memory-centric coordination for managing trading bots, research assistants, and operational tasks.
Included Assets
- AGENTS.md: Agent behaviors, delegation rules, and coordination workflow.
- MEMORY.md: Active project summaries, operational rules, constraints, and recent session logs.
- SOUL.md: Persona definition of the lead agent "Maaraa"—governing traits, boundaries, and core truths.
- TOOLS.md: Details on local tools, web search scripts, memory extraction, and maintenance workflows.
- Project: autopilot-trader/executor:
README.md: Documentation for a Lighter.xyz futures trading bot with trailing TP/SL and Telegram alerts.
- Skill: Baseline Kit:
- Secure baseline config generator and audit tool for OpenClaw environments (
skills/baseline-kit/).
- Secure baseline config generator and audit tool for OpenClaw environments (
- Skill: Deep Research Pro:
- Multi-source deep research capability using DuckDuckGo; produces structured, cited reports (
skills/deep-research-pro/).
- Multi-source deep research capability using DuckDuckGo; produces structured, cited reports (
- Memory and Documentation:
- Daily and special memory files, session logs, technical analysis reports, and resource notes.
How to Use
- Agent Coordination:
- Refer to
AGENTS.mdfor initializing sessions and agent delegation rules. The lead agent, Maaraa, routes tasks and manages subagent workflows according to project and security policies.
- Refer to
- Workspace Memory:
- Reference
MEMORY.mdfor live project context, operational requirements, and past actions. - Use memory scripts in
TOOLS.mdfor searching, maintaining, and archiving historical data.
- Reference
- Trading Automation:
- Follow
projects/autopilot-trader/executor/README.mdfor setup and operation instructions of the Lighter Copilot trading bot.
- Follow
- Research Skills:
- Leverage the Deep Research Pro skill for multi-source research tasks; see its README for CLI and agent integration.
- Security & Auditing:
- Use the Baseline Kit to generate secure config templates and perform security audits on OpenClaw setups.
- Config templates and audit tooling are in
skills/baseline-kit/.
- Operational Tools:
- Scripts for web search, backup, log deduplication, and automation are described in
TOOLS.md.
- Scripts for web search, backup, log deduplication, and automation are described in
Notes
- All agent actions, especially those affecting systems or incurring costs, are gated with strict confirmation policies—agents must confirm with the primary user before proceeding on sensitive operations.
- Workspace emphasizes auditability: never work directly on production code or critical systems in the main session; always spawn subtasks and record outcomes in memory.
- The setup leverages both Python (trading bot, automation) and Node.js (skills, scripting) components.
- No external service credentials or personal data are tracked in version control.
- Review persona and operational norms in
SOUL.mdandAGENTS.mdfor correct agent behavior, boundaries, and handoff mechanics.
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