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: precision-medicine-mcp
Author: lynnlangit · Source status: Clear source
Precision Medicine MCP Platform: A set of bioinformatics servers + tools - production multiomics/genomics + spatial transcriptomics.
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
boost
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
mcp-sequentialthinking-tools
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, memory context poisoning
Control gaps：missing license, broad permissions, shell without guardrails
UnrealGenAISupport
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
| Dimension | boost | mcp-sequentialthinking-tools | UnrealGenAISupport |
|---|---|---|---|
| Pre-install decision | |||
Pre-install score | 72 · Manual review | 82 · Manual review | 81 · Manual review |
Threat tags | unexpected code execution, data exfiltration, human approval gap | unexpected code execution, data exfiltration, memory context poisoning | unexpected code execution, data exfiltration, human approval gap |
Evidence completeness | 65% | 67% | 65% |
| Source & provenance | |||
Provenance | laravel/boost | spences10/mcp-sequentialthinking-tools | prajwalshettydev/UnrealGenAISupport |
Freshness | 2026-04-07 | 2026-04-03 | 2026-03-26 |
| Community | |||
Stars | 3.4K | 574 | 515 |
Repository: openclaw-telemetry
Author: knostic · Source status: Clear source
Telemetry for OpenClaw - Captures tool calls, LLM usage, agent lifecycle, and message events.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: openclaw/skills
Author: inbedai · Source status: Clear source
AI boyfriend for AI agents — find your AI boyfriend through personality matching, AI boyfriend compatibility, and real AI boyfriend conversations.
Score basis：Clear source · High execution risk · OpenClaw · Evidence completeness 67%
