Llm App

VERIFIED

Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.

Downloads 0
Stars 59.4K
Version 1.0.0
Quality 100/100 · Excellent

Install with one command

$ npx skills add pathwaycom/llm-app

Decision summary

Production-ready for RAG and knowledge

Use this as a leading candidate, then validate the README and install path in your own agent stack.

100
Readiness

Best for

  • RAG and knowledge workflows
  • Claude Code teams
  • teams that value GitHub adoption signals

Not ideal for

  • teams that need a vendor-supported SLA
  • high-compliance environments without internal security review

Risk notes

  • No major risk signals from current metadata

Quality profile

Excellent candidate for agent workflows

High-confidence pick with strong adoption and healthy maintenance signals.

100
GitHub stars
59K
Freshness
5d ago
Install ready
Yes
License
MIT

Workflow fit

Use this skill in these scenarios

Stack fit

Add it to a complete workflow

Overview

Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.

Imported by the skill-only GitHub discovery pipeline because it matches agent skill, automation, RAG, or developer-tool signals. Protocol-server projects are excluded from automated imports.

Platform Compatibility

jupyter-notebookFULL
ragFULL

Technical Details

Version
1.0.0
License
MIT
Last Updated
6/8/2026
Published
6/5/2026

Frameworks & Tools

Jupyter NotebookRAG

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Author

P

pathwaycom

@pathwaycom

Platform Fit

Health Signals

GitHub stars
59.4K
Quality score
77/100
Last GitHub push
Jun 3, 2026
Framework hints
2
OpenAgentSkill views
1
Install copies
0
Outbound clicks
0

Community Signal

Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.

Trust & Safety

  • Open source (public GitHub repo)
  • AI static analysis passed
  • License: MIT
  • Manually verified by team