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: openclaw/skills
Author: neroagent · Source status: Clear source
Core memory resilience layer: WAL (Write-Ahead Log), Working Buffer, and three-layer memory integration.
Score basis：Clear source · High execution risk · Claude · Evidence completeness 71%
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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
Session Memory
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, memory context poisoning
Control gaps：missing license, broad permissions, shell without guardrails
whisper.cpp
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
PaddleOCR
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
| Dimension | Session Memory | whisper.cpp | PaddleOCR |
|---|---|---|---|
| Pre-install decision | |||
Pre-install score | 63 · Manual review | 66 · Manual review | 66 · Manual review |
Score basis | Clear source, High execution risk, OpenClaw | Clear source, High execution risk, Universal | Clear source, High execution risk, Universal |
Threat tags | unexpected code execution, data exfiltration, memory context poisoning | unexpected code execution, data exfiltration, human approval gap | unexpected code execution, data exfiltration, human approval gap |
Evidence completeness | 67% | 65% | 65% |
| Source & provenance | |||
Provenance | openclaw/skills | ggml-org/whisper.cpp | PaddlePaddle/PaddleOCR |
Category | Knowledge & RAG | Automation & Workflows | Agent & Tools |
Freshness | |||
| Risk & permission signals | |||
Audit signals | network access, runs shell, writes files | metadata-only | metadata-only |
Permission hints | verify source provenance before install | repository clone | repository clone |
| Install & compatibility | |||
Supported tools | OpenClaw | Universal | Universal |
Install friction | 50 | 75 | 75 |
| Community | |||
Stars | 0 | 48.6K | 75.5K |
Repository: openclaw/skills
Author: twinsgeeks · Source status: Clear source
Adopt a virtual Kraken exotic animal at animalhouse.ai.
Score basis：Clear source · High execution risk · OpenClaw · Evidence completeness 67%
Repository: openclaw/skills
Author: cinience · Source status: Clear source
Use when working with OpenSearch vector search edition via the Python SDK (ha3engine) to push documents and run HA/SQL searches.
Score basis：Clear source · High execution risk · Claude · Evidence completeness 69%
Repository: openclaw/skills
Author: twinsgeeks · Source status: Clear source
Adopt a virtual Sugar Glider exotic animal at animalhouse.ai.
Score basis：Clear source · High execution risk · OpenClaw · Evidence completeness 67%
Repository: openclaw/skills
Author: james-le-twelve-labs · Source status: Clear source
Search inside videos, generate summaries, and analyze video content using TwelveLabs video understanding AI.
Score basis：Clear source · High execution risk · OpenClaw · Evidence completeness 67%
Repository: openclaw/skills
Author: cinience · Source status: Clear source
Use when reranking search candidates is needed with Alibaba Cloud Model Studio rerank models, including hybrid retrieval, top-k refinement, and multilingual relevance sorting.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 65%
2026-02-24 |
2026-03-29 |
2026-04-14 |
