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: serena
Author: oraios · Source status: Clear source
A powerful MCP toolkit for coding, providing semantic retrieval and editing capabilities - the IDE for your agent Topics: agent, ai, ai-coding, claude, claude-code, codex, ide, jetbrains, language-server, mcp-server, pr
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
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
MCPLuceneServer
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, memory context poisoning
Control gaps：broad permissions, shell without guardrails, network without allowlist
Graveyard Protocol CLI
Execution risk：High
Threat tags：unexpected code execution, identity privilege abuse, data exfiltration
Control gaps：missing license, broad permissions, shell without guardrails
contextplus
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, memory context poisoning
Control gaps：missing license, broad permissions, shell without guardrails
| Dimension | MCPLuceneServer | Graveyard Protocol CLI | contextplus |
|---|---|---|---|
| Pre-install decision | |||
Pre-install score | 81 · Manual review | 85 · Manual review | 79 · Manual review |
Score basis | Clear source, High execution risk, Universal | Clear source, High execution risk, OpenClaw | Clear source, High execution risk, Universal |
Threat tags | unexpected code execution, data exfiltration, memory context poisoning | unexpected code execution, identity privilege abuse, data exfiltration | unexpected code execution, data exfiltration, memory context poisoning |
Control gaps | broad permissions, shell without guardrails, network without allowlist | missing license, broad permissions, shell without guardrails | missing license, broad permissions, shell without guardrails |
Permission summary | Permission review, Network, Command | Permission review, Network, Secrets, Command | Permission review, Network, Command |
| Source & provenance | |||
Provenance | mirkosertic/MCPLuceneServer | openclaw/skills | ForLoopCodes/contextplus |
Category | Knowledge & RAG | Dev & Engineering | Knowledge & RAG |
Freshness | |||
| Risk & permission signals | |||
Audit signals | No explicit signals | needs credentials, network access, runs shell, writes files | No explicit signals |
Permission hints | repository clone, local runtime dependencies | requires binary: node, requires binary: npx, requires binary: gp-cli, verify source provenance before install | repository clone, local runtime dependencies |
| Install & compatibility | |||
Supported tools | Universal | OpenClaw | Universal |
Install friction | 40 | 65 | 40 |
| Community | |||
Stars | 3 | 0 | 1.7K |
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 · High execution risk · Universal · Evidence completeness 69%
Repository: neurodivergent-memory
Author: jmeyer1980 · Source status: Clear source
A TypeScript-based MCP server implementing a memory system inspired by neurodivergent cognitive styles.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: Buddy
Author: is-leeroy-jenkins · Source status: Clear source
An AI for federal financial management designed to support Financial Analysts, Managers, and Policy Professionals.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: langchain4j
Author: langchain4j · Source status: Clear source
LangChain4j is an open-source Java library that simplifies the integration of LLMs into Java applications through a unified API, providing access to popular LLMs and vector databases.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: neuron-ai
Author: neuron-core · Source status: Clear source
The PHP Agentic Framework to build production-ready AI driven applications.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
2026-04-01 |
2026-03-31 |
2026-04-07 |
