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ruiyongwang

Oclaw Hermes

by ruiyongwang · GitHub ↗ · v3.0.0 · MIT-0
cross-platform ⚠ suspicious
115
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0
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1
Active Installs
2
Versions
Install in OpenClaw
/install oclaw-hermes
Description
OpenClaw × Hermes × DeerFlow 三位一体智能体桥接方案 - 实现 mflow 记忆流同步、智能体集群协作、深度研究链和专家蒸馏。让 OpenClaw、Hermes、DeerFlow 的边界,成为你能力的延伸。
Usage Guidance
This package appears to be a substantial bridge/orchestration project that will create local databases, write files under your home directory, and run Docker containers that connect to local and remote services. However, the registry metadata incorrectly claims no required environment variables or config paths while the SKILL.md, docker-compose.yml, and scripts clearly require multiple API keys and will persist memory data. Before installing: 1) do not supply high-privilege tokens (e.g., full cloud credentials); create least-privilege/test tokens instead; 2) review the .env.example and every script for endpoints and persistence locations (~/.openclaw, ~/.hermes, ~/.oclaw-hermes); 3) inspect the Docker images (nousresearch/hermes, bytedance/deerflow) you will pull—prefer pinned image digests and official images; 4) run in an isolated environment or VM first (to avoid leaking secrets or contaminating your real home config); 5) confirm the repository source and maintainership (the registry lists source unknown but SKILL.md references a GitHub repo); and 6) if you need this functionality, ask the author to correct the registry metadata (declare required env vars and config paths) and to provide a minimal test mode that doesn't auto-persist or auto-publish. The mismatches raise enough concern to pause installation until you verify secrets, image provenance, and the exact runtime behavior.
Capability Analysis
Type: OpenClaw Skill Name: oclaw-hermes Version: 3.0.0 The oclaw-hermes bundle is a comprehensive integration framework designed to bridge OpenClaw with the Hermes memory system and DeerFlow multi-agent orchestration. Its core functionality involves a 'Memory Flow' (mflow) engine that captures, categorizes, and synchronizes conversation history and 'expert' insights across platforms using local SQLite storage and configurable API endpoints. While the scripts utilize high-privilege capabilities such as file system access (writing to ~/.oclaw-hermes), network requests (syncing to local/remote services), and shell execution (checking service status via subprocess), these actions are transparently documented and strictly serve the stated purpose of the architecture. The presence of hardcoded Windows file paths in some scripts suggests a specific development environment rather than malicious intent.
Capability Tags
crypto
Capability Assessment
Purpose & Capability
The skill claims to bridge OpenClaw, Hermes, and DeerFlow (expected to need local services, containers, and tokens), but the registry metadata lists no required environment variables or config paths. In reality SKILL.md, docker-compose.yml, and multiple scripts reference and require tokens/URLs (OPENCLAW_TOKEN, OPENROUTER_API_KEY, ANTHROPIC_API_KEY, DEERFLOW_*), and write to home config directories (~/.openclaw, ~/.hermes, ~/.oclaw-hermes). The omission in metadata is an incoherence: either the metadata is incomplete or the skill is hiding required privileges.
Instruction Scope
SKILL.md explicitly instructs cloning a GitHub repo, creating a .env with API keys, running docker-compose to pull/run multiple containers, and running Python scripts. These instructions will create persistent DBs and memory files and may push data to OpenClaw/Hermes/DeerFlow endpoints. The actions (running containers, creating files under user home, requiring tokens) are coherent for a bridge/orchestrator but grant broad local persistence and network access; the SKILL.md also references commands (e.g., python scripts/verify.py) not present in the manifest, which is a minor inconsistency.
Install Mechanism
No formal install spec in the registry (instruction-only), but the project includes docker-compose that will pull images (nousresearch/hermes, bytedance/deerflow) and build local Dockerfiles. There are no obscure download URLs in the package itself, but running docker-compose will fetch external container images—this is expected for this type of project but increases risk surface (third-party images, network pulls).
Credentials
Registry metadata claims no required env vars, yet SKILL.md, docker-compose.yml, and scripts require multiple credentials and service URLs (OPENCLAW_TOKEN, OPENROUTER_API_KEY, ANTHROPIC_API_KEY, DEERFLOW_GATEWAY_URL, DEERFLOW_LANGGRAPH_URL, etc.). The code also reads/writes to local config paths and persistent DBs under user home. Requesting multiple unrelated model-provider keys and platform tokens is reasonable for a multi-platform bridge, but the mismatch with declared requirements and lack of explicit justification is a red flag.
Persistence & Privilege
The skill will create persistent artifacts (SQLite DBs in ~/.openclaw/.oclaw-hermes, files under ~/.hermes, Docker containers and volumes) and can sync memories across platforms. It does not set always:true, but it does request persistent local storage and may auto-register/publish skills per config options. Persistence and container orchestration are expected for this use case but increase blast radius; verify storage locations and retention policy before use.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install oclaw-hermes
  3. After installation, invoke the skill by name or use /oclaw-hermes
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v3.0.0
oclaw-hermes v3.0.0 is a major update with deep system fusion, memory-driven routing, and new unified architecture. - Introduced UnifiedCore to deeply merge OpenClaw, Hermes, and DeerFlow systems. - Added mflow v2.0: five-layer memory flow for real-time, cross-platform memory synchronization. - Implemented memory-driven agent routing and Skill-memory dual enhancement. - Expanded agent cluster to six core roles (Lead/Research/Code/Browser/Memory/Skill). - Enabled automatic memory extraction and graph-based memory reasoning. - Added scripts: auto_memory.py, mflow_v2.py, store_memory.py, and unified_core.py. - Updated documentation to reflect new architecture and features.
v2.0.0
**Major update: oclaw-hermes 2.0.0 integrates OpenClaw, Hermes, and DeerFlow, unlocking seamless multi-agent collaboration and advanced research capabilities.** - Introduces unified memory synchronization (mflow) across OpenClaw, Hermes, and DeerFlow. - Adds multi-agent cluster management with roles like Lead, Research, Code, Browser, Skill, Memory, and Expert Agent. - Supports deep research chains for one-click advanced topic analysis and report generation. - Provides local and Docker deployment options, with detailed configuration for skills, agents, and LLM providers. - Includes command-line and Python API interfaces for messaging, research, expertise distillation, and memory sync. - Enhanced skill ecosystem integration and expert knowledge distillation.
Metadata
Slug oclaw-hermes
Version 3.0.0
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 2
Frequently Asked Questions

What is Oclaw Hermes?

OpenClaw × Hermes × DeerFlow 三位一体智能体桥接方案 - 实现 mflow 记忆流同步、智能体集群协作、深度研究链和专家蒸馏。让 OpenClaw、Hermes、DeerFlow 的边界,成为你能力的延伸。 It is an AI Agent Skill for Claude Code / OpenClaw, with 115 downloads so far.

How do I install Oclaw Hermes?

Run "/install oclaw-hermes" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Oclaw Hermes free?

Yes, Oclaw Hermes is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Oclaw Hermes support?

Oclaw Hermes is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Oclaw Hermes?

It is built and maintained by ruiyongwang (@ruiyongwang); the current version is v3.0.0.

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