Compare skills
Pick 2–4 skills and compare what really matters: fit, risk, install effort, and community signal.
Selected skills (2/4)
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
Repository: spring-ai-playground
Author: JM-Lab · Source status: Clear source
A self-hosted web UI that simplifies AI experimentation and testing for Java developers.
Score basis：Clear source · High risk signals · Universal
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
langchain4j
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, memory context poisoning
Control gaps：missing license, broad permissions, shell without guardrails
agent-memory-systems
Execution risk：High
Threat tags：data exfiltration, memory context poisoning, human approval gap
Control gaps：missing license, network without allowlist, no human approval
| Dimension | langchain4j | agent-memory-systems |
|---|---|---|
| SAS-v2.1 pre-install audit | ||
Audit grade | C · Review first | C · Review first |
Execution risk | High | High |
Threat tags | unexpected code execution, data exfiltration, memory context poisoning | data exfiltration, memory context poisoning, human approval gap |
Control gaps | missing license, broad permissions, shell without guardrails | missing license, network without allowlist, no human approval |
Permission summary | Permission review, Network, Command | Network, Command |
Evidence confidence | 67% | 65% |
| Source & provenance | ||
Provenance | langchain4j/langchain4j | davila7/claude-code-templates/tree/main/cli-tool/components/skills/ai-research/agent-memory-systems |
Category | Knowledge & RAG | Knowledge & RAG |
Freshness | 2026-04-08 | |
| Risk & trust | ||
Trust score | 81 | 79 |
Audit signals | No explicit signals | No explicit signals |
Permission hints | ||
| Install & compatibility | ||
Supported tools | Universal | Claude, Codex, Cursor, Universal |
Install method | script-backed | registry-install |
Install friction | 40 | |
| Community | ||
Stars | 11.5K | 19.9K |
Repository: openpencil
Author: ZSeven-W · Source status: Clear source
The world's first open-source AI-native vector design tool and the first to feature concurrent Agent Teams.
Score basis：Clear source · Low risk signals · Universal
Repository: cymbal-air-toolbox-demo
Author: GoogleCloudPlatform · Source status: Clear source
Demo of a customer service agent (Cymbal Air) using LangGraph, Tools, and RAG to interact with Google Cloud Databases via MCP Toolbox.
Score basis：Clear source · Low risk signals · Universal
Repository: scholar-rag
Author: PangHu1020 · Source status: Clear source
A beginner-friendly and extensible Agentic RAG project that demonstrates the full pipeline of document parsing, retrieval, reranking, workflow orchestration, tool calling, and answer generation, designed for both learnin
Score basis：Clear source · Low risk signals · Universal
Repository: OpenViking
Author: volcengine · Source status: Clear source
OpenViking is an open-source context database designed specifically for AI Agents(such as openclaw).
Score basis：Clear source · Risk needs review · Universal
repository clone, local runtime dependencies |
registry access, remote metadata pull, runtime dependencies may be required |
50 |
