C — Moderate risk signals Graded October 16, 2026Several concerns worth a closer look before you install.Based on public adoption and transparency signals as of October 16, 2026. Our opinion, not a code audit or security guarantee.
AI agent skill · Developer tools
awesome-openclaw-tutorial
OpenClaw 中文教程(4500+ Star · 已出版纸质书):安装、配置、Skills、飞书接入与避坑|作者的 GPT-6 / Codex / Claude Code 新项目见 README 顶部
Bottom line: Signal-based grade (3/7 points): well starred on GitHub, public source code. This reflects adoption and transparency, not a code review.
- Popularity score
- 41/100
- Rank
- #291 of 500
- GitHub stars
- 4.6k
What it does
Comprehensive Chinese-language tutorial for OpenClaw, an AI agent framework, covering installation, configuration, skills development, Feishu (Lark) integration, and common pitfalls. Includes examples for GPT-6, Codex, and Claude Code projects with 4500+ GitHub stars and published print edition.
Who it’s for
Chinese-speaking builders and executives implementing OpenClaw-based AI agents, particularly those integrating with Feishu workplace collaboration tools. Best suited for teams that read Chinese fluently and want production deployment guidance.
Copy-paste setup
Check these steps against the project’s own instructions before running anything.
Verify against the repo README at https://github.com/xianyu110/awesome-openclaw-tutorial (opens external site) for current setup instructions. The repository appears to be a documentation/tutorial resource rather than an npm package, so installation typically involves cloning the repo and following markdown guides. Specific npx or config snippet availability should be confirmed in the repository's README section.
Risks
- Credential exposure in tutorials: Code examples may inadvertently show patterns for storing API keys or Feishu tokens; verify no hardcoded secrets in sample configurations before production use.
- Third-party framework dependency: Security posture depends on OpenClaw framework maintenance and Feishu API stability; monitor upstream for vulnerabilities.
- Language barrier to updates: Chinese-only documentation may delay security advisory dissemination to non-Chinese speakers on your team.
- Prompt injection via skills: Custom skill examples may not cover input validation best practices; sanitize user inputs when extending agent capabilities.
- Integration scope creep: Feishu integration patterns could over-privilege agent access to workplace data; enforce least-privilege permissions at the connector level.
How to stay secure
Security Hardening Guide: Awesome-OpenClaw-Tutorial
Least-privilege permissions
- Feishu access tokens: Create a dedicated service account (a special login just for the AI agent) with only the permissions it actually needs—for example, if the agent only reads messages, don't give it permission to delete files or modify settings.
- API key scoping: When creating API keys for OpenClaw skills, restrict each key to its specific function (e.g., one key for translations only, another for scheduling) rather than one master key that can do everything.
- Audit connector settings: Review what data the Feishu connector can access (documents, contacts, calendar) quarterly and disable access to any data the agent no longer needs.
Network isolation
- Avoid hardcoded secrets: Never copy example code that shows API keys or tokens directly in configuration files; use environment variables or secure secret management tools instead (like encrypted vaults).
- Monitor third-party updates: Subscribe to OpenClaw and Feishu security advisories; outdated frameworks can contain known exploitable weaknesses, so update regularly and test changes in a staging environment first.
- Test in controlled environments: Try new tutorials and configurations in a sandbox (isolated test area) before deploying to production systems that handle real business data.
Monitoring
- Log skill activities: Enable detailed logging of what each custom skill does (inputs it receives, data it accesses) and review logs weekly for unexpected behavior.
- Watch for injection attempts: Monitor agent inputs for suspicious patterns like unusual commands or attempts to manipulate the system—these may indicate someone testing your security.
- Language-aware updates: Assign at least one team member to track Chinese-language OpenClaw security notices, and translate critical alerts for your entire team to ensure nothing gets missed.
Red flags to watch for
- Skills requesting unexpected data: If a tutorial example asks the agent to access employee personal files or communication logs beyond what's necessary, exclude that capability.
- Overpermissioned agent responses: If the agent starts taking actions it wasn't designed for (deleting messages, modifying settings, accessing restricted groups), immediately disable the skill and investigate.
- Poor input validation in examples: If tutorial code doesn't check or clean user input before processing, add validation (filter for dangerous commands) when you implement it yourself.
Alternatives
- LangChain (opens external site) — Multi-language agent framework with extensive documentation and community examples.
- AutoGPT (opens external site) — Open-source autonomous agent with English-first tutorials and skill plugins.
- Dify (opens external site) — Low-code AI agent platform with built-in integration patterns (Chinese + English docs).
- n8n (opens external site) — Workflow automation with agent capabilities and visual skill builder.