No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by forcedotcom · Agent Tool · ★ 1.1k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is sf-skills safe to install? View the security audit →
Salesforce Skills Library This repository provides a curated collection of Salesforce agent skills for building applications. It includes skills for Agentforce agents, Lightning apps, Flow, Apex, SOQL, Lightning Web Components (LWC), UI bundles, objects and fields, permission sets, and related areas. The skills are contributed by Salesforce and the broader community. It’s optimized for Agentforce Vibes and can be used with any AI tool that supports skills. 🗂️ Structure 🚀 Usage 📦 Samples The folder contains synced sample apps. For example, tracks the npm package (nightly and on manual trigger via GitHub Actions). To run the same sync locally from the repository root: The GitHub Action runs the same commands and
| Stars | 1,068 |
| Forks | 363 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 60.0927338102283/100 |
| Open Issues | 37 |
| Last Updated | 2026-10-09 |
| Created | 2025-11-07 |
| Platforms | python |
| Est. Tokens | ~14k |
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sf-skills is Salesforce's curated collection of agent skills for building applications. Optimized for Agentforce Vibes, compatible with all AI tools.. It is categorized as a Agent Tool with 1.1k GitHub stars.
sf-skills is primarily written in Python.
You can find installation instructions and usage details in the sf-skills GitHub repository at github.com/forcedotcom/sf-skills. The project has 1.1k stars and 363 forks, indicating an active community.
sf-skills is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to sf-skills on Agent Skills Hub include excalidraw-diagram-skill, raptor, chinese-novelist-skill. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: