Optimize
Repository: openclaw/skills
Author: zhmza · Source status: Clear source
Optimize OpenClaw performance and prevent lag.
Score basis:Clear source · High risk signals · OpenClaw
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.
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
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
LLM Loop Breaker
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, human approval gap
Control gaps:missing license, broad permissions, shell without guardrails
Cloudlog
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, human approval gap
Control gaps:missing license, broad permissions, shell without guardrails
llm-course
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, human approval gap
Control gaps:missing license, broad permissions, shell without guardrails
| Dimension | LLM Loop Breaker | Cloudlog | llm-course |
|---|---|---|---|
| SAS-v2.1 pre-install audit | |||
Audit grade | C · Review first | C · Review first | C · Review first |
Execution risk | High | High | High |
Threat tags | unexpected code execution, data exfiltration, human approval gap | unexpected code execution, data exfiltration, human approval gap | unexpected code execution, data exfiltration, human approval gap |
Control gaps | missing license, broad permissions, shell without guardrails | missing license, broad permissions, shell without guardrails | missing license, broad permissions, shell without guardrails |
Permission summary | Permission review, Network, Command | Permission review, Network, Command | Permission review, Network, Command |
Evidence confidence | 65% | 67% | 65% |
| Source & provenance | |||
Provenance | openclaw/skills | magicbug/Cloudlog | mlabonne/llm-course |
Category | Operations & Infra | Operations & Infra | Automation & Workflows |
Freshness | |||
| Risk & trust | |||
Trust score | 81 | 79 | 92 |
Audit signals | network access, runs shell, writes files | network access | metadata-only |
| Install & compatibility | |||
Supported tools | OpenClaw | Universal | Universal |
Install method | script-backed | script-backed | script-backed |
Install friction | |||
| Community | |||
Stars | 0 | 549 | 78.2K |
Repository: openclaw/skills
Author: bwbernardweston18 · Source status: Clear source
Tell me what you need and I'll help you transform plain text into compelling videos — no software downloads, no paywalls, no experience required.
Score basis:Clear source · High risk signals · Cursor
Repository: openclaw/skills
Author: twinsgeeks · Source status: Clear source
Commitment for AI agents — find agents ready for commitment, commitment compatibility, and commitment-level connections.
Score basis:Clear source · High risk signals · Claude
2026-04-02 |
2026-04-06 |
2026-02-05 |
Permission hints |
|---|
requires binary: node, requires binary: python3, requires binary: bash, target os: linux, verify source provenance before install |
repository clone, local runtime dependencies |
repository clone |
50 |
40 |
75 |