Individual skill

langchain-debug-bundle

Not available

plugins/saas-packs/langchain-py-pack/skills/langchain-debug-bundle/SKILL.md

Read pinned source

Source commit 0500b275e963c027f6b410e8c49c0446945c574e

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
No
Repository scan complete
No
Skill scan complete
No
Observed behavior
Not checked yet
Last checked
Nov 12, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

Standard SKILL.md format has not been attested at this commit. No installation command is available; inspect the source.

Repository context

Repository stars (not skill ratings)
2,916
Repository last updated
Nov 12, 2026
License
MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt
# LangChain Debug Bundle (Python)

## Overview

An on-call engineer pages you at 2am: the production agent loops, `ToolMessage`
outputs are empty strings, the user sees "I could not find the answer." Someone
asks the right question — *what state was the graph in when it gave up?* — and
there is no answer, because the terminal that caught the failure is already
gone, the Kubernetes pod has restarted, and the LangSmith URL was never
recorded.

This skill produces one artifact: a single `bundle-<incident_id>.tar.gz` (typically
1-10 MB) containing everything a second engineer needs to reproduce the failure
without a live terminal — environment and version manifest, filtered
`astream_events(version="v2")` JSONL, a propagating callback stack, the
Back to top