a5c-ai/langchain-tools
library/specializations/ai-agents-conversational/skills/langchain-tools/SKILL.md
LangChain tool creation and integration utilities for agent systems
$ install --global
skillsauthnpx skillsauth add a5c-ai/babysitter langchain-toolsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
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OSV-ScannerOpen Source Vulnerability database check
50%
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OWASP Dep-Check
50%
Last scanned: Apr 1, 2026, 12:56 PM61.4s2 files scanned
SKILL.md
- name:
- langchain-tools
- description:
- LangChain tool creation and integration utilities for agent systems
LangChain Tools Skill
Capabilities
- Create custom LangChain tools with proper schemas
- Integrate existing tools and APIs
- Design tool descriptions for optimal LLM understanding
- Implement structured tool inputs with Pydantic
- Handle tool errors and fallbacks
- Create tool chains and pipelines
Target Processes
- custom-tool-development
- function-calling-agent
Implementation Details
Tool Creation Patterns
- @tool decorator: Simple function-based tools
- StructuredTool: Tools with complex input schemas
- BaseTool subclass: Full control over tool behavior
- Tool from functions: Dynamic tool creation
Configuration Options
- Tool name and description
- Input schema (args_schema)
- Return type specification
- Error handling strategy
- Async/sync execution modes
Best Practices
- Clear, action-oriented descriptions
- Explicit input parameter documentation
- Proper error messages for LLM understanding
- Idempotent operations where possible
Dependencies
- langchain-core
- pydantic
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