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
Repository: llm-course
Author: mlabonne · Source status: Clear source
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 65%
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
FastChat
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
qdrant-loader
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, memory context poisoning
Control gaps：missing license, broad permissions, shell without guardrails
litellm
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
| Dimension | FastChat | qdrant-loader | litellm |
|---|---|---|---|
| Pre-install decision | |||
Pre-install score | 92 · Manual review | 81 · Manual review | 92 · Manual review |
Threat tags | unexpected code execution, data exfiltration, human approval gap | unexpected code execution, data exfiltration, memory context poisoning | unexpected code execution, data exfiltration, human approval gap |
Evidence completeness | 65% | 67% | 67% |
| Source & provenance | |||
Provenance | lm-sys/FastChat | martin-papy/qdrant-loader | BerriAI/litellm |
Category | Automation & Workflows | Knowledge & RAG | Automation & Workflows |
Freshness | |||
| Risk & permission signals | |||
Audit signals | metadata-only | writes files | metadata-only |
Permission hints | repository clone | repository clone, local runtime dependencies | repository clone |
| Install & compatibility | |||
Install friction | 75 | 40 | 75 |
| Community | |||
Stars | 39.4K | 37 | 43.2K |
Repository: vllm
Author: vllm-project · Source status: Clear source
A high-throughput and memory-efficient inference and serving engine for LLMs
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: context7
Author: upstash · Source status: Clear source
Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
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: playwright
Author: microsoft · Source status: Clear source
Playwright is a framework for Web Testing and Automation.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 65%
2025-06-02 |
2026-04-06 |
2026-04-14 |
