Score breakdown0 Version history1 Source
Category Weight Category score Contribution
Security prompt, exec, net, exfil, eval
35%
100
35.0 pts
Supply chain hash, typosquat, maintainer, lockfile
20%
100
20.0 pts
Maintenance staleness, pinning, CI
15%
100
15.0 pts
Transparency SKILL.md, perms, README
15%
100
15.0 pts
Community installs, verify, response
15%
100
15.0 pts
Findings & checks · 0 flagged
Security score 100 · 0 findings
✓ — All security checks passedNo findings in this category for the latest scan. pass
Supply chain score 100 · 0 findings
✓ — All supply chain checks passedNo findings in this category for the latest scan. pass
Maintenance score 100 · 0 findings
✓ — All maintenance checks passedNo findings in this category for the latest scan. pass
Transparency score 100 · 0 findings
✓ — All transparency checks passedNo findings in this category for the latest scan. pass
Community score 100 · 0 findings
✓ — All community checks passedNo findings in this category for the latest scan. pass
Every scanned point with the score it earned and what moved between them.
1 scans · 90 days d97a2e4 latest
Jun 23, 2026 100 d97a2e4
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
library/specializations/ai-agents-conversational/skills/langchain-react-agent/SKILL.md · 1 file library/specializations/ai-agents-conversational/skills/langchain-react-agent/SKILL.md 1.3 KB · Markdown Rendered Raw ⧉ Copy
name : langchain-react-agent
description : LangChain ReAct agent implementation with tool binding for reasoning and action loops
allowed-tools :
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LangChain ReAct Agent Skill Capabilities Implement ReAct (Reasoning + Acting) agent patterns using LangChain Configure tool binding and function calling for agents Design thought-action-observation loops Integrate with various LLM providers (OpenAI, Anthropic, etc.) Handle agent memory and state persistence Implement error handling and retry logic for agent actions Target Processes react-agent-implementation function-calling-agent Implementation Details Core Components Agent Executor Setup : Configure LangChain AgentExecutor with appropriate settingsTool Integration : Bind tools with proper schemas and descriptionsPrompt Engineering : Design system prompts for ReAct reasoning patternsOutput Parsing : Parse agent outputs and handle structured responsesConfiguration Options LLM model selection and parameters Tool definitions and schemas Memory type (buffer, summary, vector) Max iterations and timeout settings Verbose/debug mode configuration Dependencies langchain langchain-openai / langchain-anthropic Python 3.9+