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: home-assistant/core
Author: home-assistant · Source status: Clear source
:house_with_garden: Open source home automation that puts local control and privacy first.
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
anything-llm
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
graphrag
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, memory context poisoning
Control gaps：missing license, broad permissions, shell without guardrails
security-ownership-map
Execution risk：High
Threat tags：data exfiltration, human approval gap
Control gaps：missing license, broad permissions, network without allowlist
| Dimension | anything-llm | graphrag | security-ownership-map |
|---|---|---|---|
| Pre-install decision | |||
Pre-install score | 92 · Manual review | 92 · Manual review | 82 · Manual review |
Score basis | Clear source, High execution risk, Universal | Clear source, High execution risk, Universal | Clear source, High execution risk, Claude |
Execution risk | High | High | High |
Threat tags | unexpected code execution, data exfiltration, human approval gap | unexpected code execution, data exfiltration, memory context poisoning | data exfiltration, human approval gap |
Control gaps | missing license, broad permissions, shell without guardrails | missing license, broad permissions, shell without guardrails | missing license, broad permissions, network without allowlist |
Permission summary | Permission review, Network, Command | Permission review, Network, Command | Permission review, Network, Command |
Evidence completeness | 65% | 67% | 67% |
| Source & provenance | |||
Provenance | Mintplex-Labs/anything-llm | microsoft/graphrag | openai/skills/tree/main/skills/.curated/security-ownership-map |
Category | Automation & Workflows | Automation & Workflows | Data & Analytics |
Freshness | |||
| Risk & permission signals | |||
Audit signals | metadata-only | metadata-only | writes files |
Permission hints | repository clone | repository clone | registry access, remote metadata pull, runtime dependencies may be required |
| Install & compatibility | |||
Supported tools | Universal | Universal | Claude, Codex, Cursor, Universal |
Install method | script-backed | script-backed | registry-install |
Install friction | |||
| Community | |||
Stars | 58.3K | 32.2K | 7.3K |
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: 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 · 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%
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: 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%
2026-04-14 |
2026-04-14 |
2026-02-11 |
75 |
75 |
50 |
