graphrag
Repository: graphrag
Author: microsoft · Source status: Clear source
A modular graph-based Retrieval-Augmented Generation (RAG) system
Score basis:Clear source · High execution risk · Universal · Evidence completeness 67%
Compare skills
Pick 2–4 skills and compare what really matters: fit, risk, install effort, and community signal.
Comparison matrix
Highlights show current best; tooltip explains diff/best rules.
Score-basis diff rules / risk tag notes
Start with the matrix. Open this section when you need to understand audit grades, top threats, control gaps, and best-value highlights.
Suggested baseline
Search to add skills, or paste 2–4 comma-separated slugs.
How differences are detected
A row is marked different when selected skills have distinct values. Only-differences mode hides rows that are identical.
How best values are highlighted
Pre-install score, evidence completeness, and community signal prefer higher values; execution risk and install friction prefer lower values.
How to read risk tags
Risk tags come from SAS-v2.1 public-evidence signals and point to command, network, secret, context, or supply-chain items to review before install.
Selected audit signals
RAG_Techniques
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, memory context poisoning
Control gaps:missing license, broad permissions, shell without guardrails
ragflow
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, memory context poisoning
Control gaps:missing license, broad permissions, shell without guardrails
pathway
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, memory context poisoning
Control gaps:missing license, broad permissions, shell without guardrails
| Dimension | RAG_Techniques | ragflow | pathway |
|---|---|---|---|
| Pre-install decision | |||
Pre-install score | 92 · Manual review | 92 · Manual review | 92 · Manual review |
Score basis | Clear source, High execution risk, Universal | Clear source, High execution risk, Universal | Clear source, High execution risk, Universal |
Execution risk | High | High | High |
Threat tags | unexpected code execution, data exfiltration, memory context poisoning | unexpected code execution, data exfiltration, memory context poisoning | unexpected code execution, data exfiltration, memory context poisoning |
Control gaps | missing license, broad permissions, shell without guardrails | missing license, broad permissions, shell without guardrails | missing license, broad permissions, shell without guardrails |
Permission summary | Permission review, Network, Command | Permission review, Network, Command | Permission review, Network, Command |
Evidence completeness | 67% | 67% | 67% |
| Source & provenance | |||
Provenance | NirDiamant/RAG_Techniques | infiniflow/ragflow | pathwaycom/pathway |
Category | Automation & Workflows | Agent & Tools | Automation & Workflows |
Freshness | |||
| Risk & permission signals | |||
Audit signals | metadata-only | metadata-only | metadata-only |
Permission hints | repository clone | repository clone | repository clone |
| Install & compatibility | |||
Supported tools | Universal | Universal | Universal |
Install method | script-backed | script-backed | script-backed |
Install friction | |||
| Community | |||
Stars | 26.8K | 78K | 63.5K |
Repository: FastGPT
Author: labring · Source status: Clear source
FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letting you easily devel…
Score basis:Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: LightRAG
Author: HKUDS · Source status: Clear source
[EMNLP2025] "LightRAG: Simple and Fast Retrieval-Augmented Generation"
Score basis:Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: llm-app
Author: pathwaycom · Source status: Clear source
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data.
Score basis:Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: quivr
Author: QuivrHQ · Source status: Clear source
Opiniated RAG for integrating GenAI in your apps 🧠 Focus on your product rather than the RAG.
Score basis:Clear source · High execution risk · Universal · Evidence completeness 67%
2026-04-12 |
2026-04-14 |
2026-04-14 |
75 |
75 |
75 |