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.
SAS-v2.1 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
Audit score, evidence confidence, trust score, 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
HuixiangDou
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
tool_calling_api
Execution risk：High
Threat tags：prompt injection, tool poisoning, unexpected code execution
Control gaps：missing license, broad permissions, shell without guardrails
agentic-ai-engineering
Execution risk：High
Threat tags：prompt injection, tool poisoning, unexpected code execution
Control gaps：missing license, broad permissions, shell without guardrails
| Dimension | HuixiangDou | tool_calling_api | agentic-ai-engineering |
|---|---|---|---|
| SAS-v2.1 pre-install audit | |||
Threat tags | unexpected code execution, data exfiltration, human approval gap | prompt injection, tool poisoning, unexpected code execution | prompt injection, tool poisoning, unexpected code execution |
Evidence confidence | 65% | 67% | 68% |
| Source & provenance | |||
Provenance | InternLM/HuixiangDou | Shuyib/tool_calling_api | agenticloops-ai/agentic-ai-engineering |
Category | Automation & Workflows | Dev & Engineering | Dev & Engineering |
Freshness | |||
| Risk & trust | |||
Trust score | 92 | 82 | 82 |
Audit signals | metadata-only | No explicit signals | No explicit signals |
| Install & compatibility | |||
Install friction | 75 | 40 | 40 |
| Community | |||
Stars | 2.5K | 20 | 49 |
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 · Risk needs review · Universal
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 · Risk needs review · Universal
Repository: anything-llm
Author: Mintplex-Labs · Source status: Clear source
The all-in-one AI productivity accelerator.
Score basis：Clear source · Risk needs review · Universal
Repository: MoneyPrinterTurbo
Author: harry0703 · Source status: Clear source
利用AI大模型，一键生成高清短视频 Generate short videos with one click using AI LLM.
Score basis：Clear source · Risk needs review · Universal
Repository: litellm
Author: BerriAI · Source status: Clear source
Python SDK, Proxy Server (AI Gateway) to call 100+ LLM APIs in OpenAI (or native) format, with cost tracking, guardrails, loadbalancing and logging.
Score basis：Clear source · Risk needs review · Universal
2025-11-24 |
2026-03-28 |
2026-04-07 |
Permission hints |
|---|
repository clone |
repository clone, local runtime dependencies |
repository clone, local runtime dependencies |
