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
claude-supermemory
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, memory context poisoning
Control gaps：missing license, broad permissions, shell without guardrails
mcp-mindmesh
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 | claude-supermemory | mcp-mindmesh | litellm |
|---|---|---|---|
| SAS-v2.1 pre-install audit | |||
Threat tags | unexpected code execution, data exfiltration, memory context poisoning | unexpected code execution, data exfiltration, memory context poisoning | unexpected code execution, data exfiltration, human approval gap |
| Source & provenance | |||
Provenance | supermemoryai/claude-supermemory | 7ossamfarid/mcp-mindmesh | BerriAI/litellm |
Category | Automation & Workflows | Integrations & Connectors | Automation & Workflows |
Freshness | 2026-03-06 | 2026-04-06 | 2026-04-14 |
| Risk & trust | |||
Trust score | 92 | 81 | 92 |
Audit signals | |||
| Install & compatibility | |||
Install friction | 75 | 40 | 75 |
| Community | |||
Stars | 2.5K | 5 | 43.2K |
Repository: claude-code-router
Author: musistudio · Source status: Clear source
Use Claude Code as the foundation for coding infrastructure, allowing you to decide how to interact with the model while enjoying updates from Anthropic.
Score basis：Clear source · Risk needs review · Universal
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: pathway
Author: pathwaycom · Source status: Clear source
Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
Score basis：Clear source · Risk needs review · Universal
No explicit signals |
metadata-only |
Permission hints | repository clone | repository clone, local runtime dependencies | repository clone |
|---|
