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: conductor
Author: conductor-oss · Source status: Clear source
Conductor is an event driven agentic orchestration platform providing durable and highly resilient execution engine for applications and AI Agents
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
dify
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
ArcGIS-JavaScript-AI-Component
Execution risk：High
Threat tags：unexpected code execution, identity privilege abuse, data exfiltration
Control gaps：missing license, broad permissions, shell without guardrails
MinerU
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
| Dimension | dify | ArcGIS-JavaScript-AI-Component | MinerU |
|---|---|---|---|
| Pre-install decision | |||
Pre-install score | 92 · Manual review | 82 · Manual review | 92 · Manual review |
Threat tags | unexpected code execution, data exfiltration, human approval gap | unexpected code execution, identity privilege abuse, data exfiltration | unexpected code execution, data exfiltration, human approval gap |
Permission summary | Permission review, Network, Command | Permission review, Network, Secrets, Command | Permission review, Network, Command |
Evidence completeness | 65% | 67% | 65% |
| Source & provenance | |||
Provenance | langgenius/dify | ralouta/ArcGIS-JavaScript-AI-Component | opendatalab/MinerU |
Category | Agent & Tools | Dev & Engineering | Agent & Tools |
Freshness | |||
| Risk & permission signals | |||
Audit signals | metadata-only | needs credentials | metadata-only |
Permission hints | repository clone | repository clone, local runtime dependencies | repository clone |
| Install & compatibility | |||
Install friction | 75 | 55 | 75 |
| Community | |||
Stars | 137.7K | 4 | 59.7K |
Repository: Warp
Author: warpdotdev · Source status: Clear source
Warp is the agentic development environment, built for coding with multiple AI agents.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: OpenBB
Author: OpenBB-finance · Source status: Clear source
Financial data platform for analysts, quants and AI agents.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 65%
Repository: OpenSpec
Author: Fission-AI · Source status: Clear source
Spec-driven development (SDD) for AI coding assistants.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 65%
Repository: ruflo
Author: ruvnet · Source status: Clear source
🌊 The leading agent orchestration platform for Claude.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
2026-04-14 |
2026-03-30 |
2026-04-14 |
