Skill 审计报告

langgraph-implementation 审计报告.

Implements stateful agent graphs using LangGraph. Use when building graphs, adding nodes/edges, defining state schemas, implementing checkpointing, handling interrupts, or creating multi-agent systems with LangGraph.

已阻止 · 阻止需审查生成于 2026年10月11日启发式元数据审计
70
审计
60
信任
62
质量
72
安全性
88
维护
92
安装

OpenAgentSkill 信任评分

60
人工审查

OpenAgentSkill 信任评分

Trust Score 帮助 Agent 在安装前判断一个 Skill 是否足以进入候选清单。

GitHub 采用度

警告

48

80 个 GitHub Stars

Star/Fork 活跃度

警告

43

80 个 Star,8 个 Fork; 当前元数据中没有议题活跃度信息

近期维护

通过

88

距上次推送 2 个月

许可证清晰度

通过

86

Apache-2.0

README/SKILL.md 完整度

信息

76

公开元数据需要更完整的 README/SKILL.md 上下文

依赖与运行时风险

警告

46

command execution surface, credential or environment access

安装可用性

通过

92

npx skills add existential-birds/beagle --skill langgraph-implementation

安装命令安全性

通过

92

标准软件包或运行时安装路径

权限范围

失败

38

secrets or environment access, shell or command execution

仓库证据

通过

86

https://github.com/existential-birds/beagle/tree/main/plugins/beagle-ai/skills/langgraph-implementation

审查状态

信息

66

可用 AI 审查数据

Agent 验证结果

信息

54

暂未有 Agent 结果数据

检查项

安装与采用审查

6 通过 · 15 需审查

安装路径

92

通过

npx skills add existential-birds/beagle --skill langgraph-implementation

仓库

88

通过

https://github.com/existential-birds/beagle/tree/main/plugins/beagle-ai/skills/langgraph-implementation

许可证

86

通过

Apache-2.0

维护

88

通过

距上次推送 2 个月

AI 审查

55

检查

The skill does not include explicit security guidance for LangGraph applications, such as protecting against prompt injection when LLM-controlled router nodes decide destinations or tool calls.

README/SKILL.md 完整度

84

通过

Usable description available

依赖风险

46

修复

command execution surface, credential or environment access

安装命令安全性

92

通过

标准软件包或运行时安装路径

权限范围

38

修复

secrets or environment access, shell or command execution

Star/Fork 活跃度

43

修复

80 个 Star,8 个 Fork; 当前元数据中没有议题活跃度信息

采用度

68

信息

80 个 GitHub Stars

警告

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • The skill does not include explicit security guidance for LangGraph applications, such as protecting against prompt injection when LLM-controlled router nodes decide destinations or tool calls.
  • Frontmatter metadata is minimal; adding tags and framework version guidance would improve discoverability and interoperability.
  • Some examples reference undefined components like `llm`, `research_agent`, and `coding_agent`, which may require additional setup context for new users.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • GitHub adoption: 80 GitHub stars
  • Stars/forks activity: 80 stars, 8 forks; issue activity unavailable in current metadata
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution

方法

本报告综合公开元数据、AI 审查输出、仓库活跃度、安装就绪度、OpenAgentSkill 事件、质量评分、信任检查和 Agent 安全门槛;它不是完整的源代码安全审计。

对比相近选项

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