B — Some risk signals Graded October 16, 2026Minor concerns worth a quick check.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, Files & documents
skill
收录最全、更新最快的技能Skills商店:精选原创技能包(涵盖文档处理、内容创作、编程开发、机器学习、自动化工作流),全部打包好可直接安装使用!同时自动抓取GitHub上万个Skills项目,按分类、更新时间、Star数量整理。The most comprehensive and frequently updated AI Agent skill library, featuring curated skill packs across document processing, content creation, programming, machine learning, automated workflows, and many more domains.
Bottom line: Signal-based grade (4/7 points): very widely starred on GitHub, public source code. This reflects adoption and transparency, not a code review.
- Popularity score
- 44/100
- Rank
- #218 of 500
- GitHub stars
- 8.2k
What it does
Aggregates a comprehensive library of AI agent skills across document processing, content creation, programming, machine learning, and workflow automation. Curates original skill packs ready for direct installation while automatically indexing thousands of Skills projects from GitHub, organized by category, update recency, and popularity.
Who it’s for
AI agent builders and developers seeking pre-built, vetted skill components to accelerate agent development. Executives evaluating skill ecosystems and capability marketplaces for enterprise AI deployments.
Copy-paste setup
Check these steps against the project’s own instructions before running anything.
Verify against the repo README at https://github.com/anbeime/skill (opens external site) for current installation instructions. Likely involves cloning the repository and installing dependencies via npm or similar package manager; exact setup steps should be confirmed in the repository's README or documentation.
Risks
- Third-party skill provenance: Auto-indexed GitHub skills lack centralized vetting, creating supply-chain risk for malicious or poorly-maintained code injection
- Credential scope creep: Individual skills may request broad permissions; no apparent standardized permission model or capability sandboxing documented
- Prompt injection vectors: Dynamically loaded skill descriptions and parameters could be manipulated to alter agent behavior if not sanitized
- Maintenance opacity: Repository does not appear to publish security policies or vulnerability disclosure processes; maintenance posture unclear
- Data handling undocumented: No visible privacy policy or audit trails regarding which agent data flows through skill execution
How to stay secure
Security Hardening Guide for AI Agent Skills
Least-privilege permissions
- Approve only what's needed: Before installing a skill, review what access it requests (files, databases, APIs). Only grant permission for the specific data or systems it actually needs to work—reject any "blanket access" requests.
- Restrict credential exposure: Store passwords and API keys in a secure vault separate from the skill itself. Never hardcode credentials into skill code or configuration files.
- Rotate access regularly: Change passwords and API keys for any systems connected to skills every 90 days, and immediately if a skill is removed or updated.
Network isolation
- Run skills in sandboxed environments: Use isolated containers or restricted execution zones so a compromised skill cannot access your broader network or other systems.
- Whitelist external connections: Only allow skills to communicate with approved external services and APIs. Block or log all other outbound network traffic.
- Separate sensitive data: Keep skills away from internal systems storing financial data, customer information, or trade secrets unless absolutely required.
Monitoring
- Log all skill activity: Record what data each skill accesses, what actions it performs, and when. Review logs weekly for unusual behavior.
- Set alerts for anomalies: Configure automatic warnings if a skill makes unexpected database queries, downloads large amounts of data, or attempts unauthorized access.
- Audit skill updates: Whenever a skill is updated, verify what changed and test it in a non-production environment first before deploying to live agents.
Red flags to watch for
- Unknown or inactive maintainers: Avoid skills from developers with no public track record, or repositories that haven't been updated in over a year without clear explanation.
- Overly broad permission requests: Be suspicious of skills asking for admin rights, unlimited file access, or permission to modify core system settings beyond their stated purpose.
- Missing documentation or security info: Do not use skills that lack clear instructions, have no visible source code, or whose creators do not publish a responsible disclosure policy for reporting vulnerabilities.
Alternatives
- OpenAI's GPT Store and official plugin ecosystem (curated by OpenAI, higher baseline trust)
- Anthropic's tool_use and official MCP ecosystem (Claude-native integrations with published standards)
- LangChain Hub (community-driven with more transparent versioning and review processes)
- Hugging Face Models and Spaces (established reputation system and model cards with usage policies)