Skip to content
TrustedSkillsbeta
Back to all skills

Langchain Debug Bundle

Listed
jeremylongshore·vlatest·ai-ml·MIT

Helps with LangChain, debugging as part of testing, debugging, and quality assurance workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add jeremylongshore/tons-of-skills-marketplace --skill langchain-debug-bundle -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

jeremylongshore

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

Nobody has reviewed this code. TrustedSkills indexes and links skills; it does not audit, run or scan them. A skill runs with whatever access you give your agent — read the source before you install it.

Automated safety checks

scanned

We could not read this skill's source, so none of the checks below were run.

Not scanned. none of the 396 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as jeremylongshore/claude-code-plugins-plus-skills.
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The langchain-debug-bundle skill provides tools for debugging LangChain applications. It allows you to inspect the intermediate steps and data flow within a LangChain chain or agent, making it easier to identify errors and understand how your application is behaving. This bundle includes components that output trace information and allow for detailed inspection of LLM calls and other operations.

When to use it

  • Troubleshooting complex chains: When an agent isn't producing the expected results, this skill helps pinpoint exactly where the process is failing.
  • Understanding data transformations: Inspect how data changes as it moves through a LangChain pipeline.
  • Debugging LLM interactions: See the full prompt and response details for each interaction with a Large Language Model (LLM).
  • Analyzing agent reasoning: Understand the steps an agent takes to arrive at a conclusion, especially in multi-step processes.

Key capabilities

  • Trace generation: Creates detailed logs of chain execution.
  • LLM call inspection: Provides visibility into prompts and responses sent to LLMs.
  • Intermediate data output: Displays the values of variables at each step of a chain or agent's process.

Example prompts

  • "Debug this LangChain chain, showing me all intermediate steps."
  • "Show me the prompt and response for the last LLM call in this agent execution."
  • "Trace the data flow through this memory object."

Tips & gotchas

  • Requires a working LangChain application to debug. The skill is designed to be integrated into existing projects, not run standalone.