Langgraph Implementation
v1.0.0Implements stateful agent graphs using LangGraph. Use when building graphs, adding nodes/edges, defining state schemas, implementing checkpointing, handling...
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byKevin Anderson@anderskev
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
The name/description match the SKILL.md: the files provide patterns and examples for building stateful agent graphs with LangGraph (nodes, edges, checkpointers, interrupts, streaming, multi-agent patterns). There are no unrelated environment variables, binaries, or install steps required by the skill itself.
Instruction Scope
Instructions stay within the domain of using LangGraph APIs and patterns. Some examples show invoking other agents/LLMs (e.g., llm.invoke, research_agent.invoke, coding_agent.invoke) and calling side-effectful placeholders (execute, dangerous_api_call). Those are illustrative and expected for orchestration examples, but if an agent actually invokes configured external LLMs, tools, or APIs at runtime this will produce network calls and side effects—the documentation itself does not supply or request those connectors.
Install Mechanism
No install spec and no code files are included; this is instruction-only so nothing is downloaded or written to disk by an installer.
Credentials
The skill declares no required environment variables or credentials. The docs reference optional checkpointers (SqliteSaver, PostgresSaver) and show a from_conn_string example — using those in real deployments would require connection strings/credentials provided elsewhere. The skill itself does not ask for secrets, which is proportionate, but users should be aware that following examples may require giving the runtime database credentials or LLM/tool connectors.
Persistence & Privilege
always is false and default autonomous invocation is allowed (normal). The skill does not request persistent agent-wide privileges or modify other skills' configs.
Scan Findings in Context
[no-regex-findings] expected: The package is instruction-only with no code files for the regex scanner to analyze; this is expected. The lack of findings is not proof of safety but consistent with an instructions-only skill.
Assessment
This skill is a documentation/instruction pack for using LangGraph and appears internally consistent. Before installing or enabling it: (1) Note that examples reference invoking other agents/LLMs and connecting to databases—if you run graphs that use those examples you will need to provide connection strings or connectors, and the agent will make external calls. (2) Because this skill is instruction-only and has no source/homepage listed, verify you trust the publisher or review the instructions thoroughly before granting any runtime credentials. (3) If you intend to allow autonomous execution, consider limiting what connectors/credentials the agent has access to (e.g., don't expose production DB credentials) and enable monitoring/logging of external calls. If you want, provide the skill's owner/source or intended runtime environment and I can call out any further specific risks.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.