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: lookupmark · Source status: Clear source
Find and send local files to a chat channel (Telegram, Discord, WhatsApp, Signal, Slack).
Score basis：Clear source · High execution risk · OpenClaw · 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
Lidarr
Execution risk：High
Threat tags：unexpected code execution, identity privilege abuse, data exfiltration
Control gaps：missing license, broad permissions, shell without guardrails
ByteRover
Execution risk：High
Threat tags：unexpected code execution, identity privilege abuse, data exfiltration
Control gaps：missing repo, missing license, broad permissions
security-ownership-map
Execution risk：High
Threat tags：data exfiltration, human approval gap
Control gaps：missing license, broad permissions, network without allowlist
| Dimension | Lidarr | ByteRover | security-ownership-map |
|---|---|---|---|
| Pre-install decision | |||
Pre-install score | 81 · Manual review | 79 · Evidence missing | 82 · Manual review |
Score basis | Clear source, High execution risk, Universal | Source needs review, High execution risk, Claude | Clear source, High execution risk, Claude |
Threat tags | unexpected code execution, identity privilege abuse, data exfiltration | unexpected code execution, identity privilege abuse, data exfiltration | data exfiltration, human approval gap |
Control gaps | missing license, broad permissions, shell without guardrails | missing repo, missing license, broad permissions | missing license, broad permissions, network without allowlist |
Permission summary | Permission review, Network, Secrets, Command | Permission review, Network, Secrets, Command | Permission review, Network, Command |
Evidence completeness | 67% | 69% | 67% |
| Source & provenance | |||
Provenance | openclaw/skills | Source needs review | openai/skills/tree/main/skills/.curated/security-ownership-map |
Category | Knowledge & RAG | Knowledge & RAG | Data & Analytics |
Freshness | |||
| Risk & permission signals | |||
Audit signals | needs credentials, network access, runs shell, writes files | needs credentials, network access, runs shell, writes files | writes files |
Permission hints | verify source provenance before install | review skill metadata before install, check required credentials in skill docs | registry access, remote metadata pull, runtime dependencies may be required |
| Install & compatibility | |||
Supported tools | Universal | Codex, OpenClaw, Claude, Cursor, Universal | Claude, Codex, Cursor, Universal |
Install method | script-backed | instruction-only | registry-install |
Install friction | |||
| Community | |||
Stars | 0 | 108 | 7.3K |
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 text embeddings are needed from Alibaba Cloud Model Studio models for semantic search, retrieval-augmented generation, clustering, or offline vectorization pipelines.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 65%
Repository: openclaw/skills
Author: cinience · Source status: Clear source
Use when multimodal embeddings are needed from Alibaba Cloud Model Studio models such as `qwen3-vl-embedding` for image, video, and text retrieval, cross-modal search, clustering, or offline vectorization pipelines.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 69%
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: eternal0404 · Source status: Clear source
The all-in-one master skill — unified interface for every capability domain.
Score basis：Clear source · High execution risk · Claude · Evidence completeness 67%
2026-04-02 |
2026-04-08 |
2026-02-11 |
65 |
100 |
50 |
