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 callawaycloud · Agent Tool · ★ 54
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is llm-apex-agents safe to install? View the security audit →
llm-apex-agents Run Large Language Model (GPT) agents in Salesforce apex. Watch Full Demo Here :shipit: What is an Agent? An “Agent” is a technique for instilling the ability for an LLM to “Reason” and take “Action”. This approach is introduced by the ReAct Paper (Reason → Act) and used in popular libraries like langchain and auto-gpt. Library Terminology : LLM/GTP model. Currently only OpenAI GPT Completion & Chat models are supported. : The communication "protocol" between the model & system. Currently only ReAct style prompts are supported. : A instance formed to solve a given objective. : The commands at the agents disposal : The act of invoking a tool Getting Started install in a scratch org () or to a developer edition () Warning Scratch & developer orgs have a limit of 5 chained queueable jobs, which will limit how much work the agent can do. Assign yourself to the permission set. Open Setup - Named Credential - External Credential - O
| Stars | 54 |
| Forks | 26 |
| Language | Apex |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 68.6808914517635/100 |
| Open Issues | 7 |
| Last Updated | 2023-04-26 |
| Created | 2023-04-07 |
| Est. Tokens | ~18k |
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llm-apex-agents is Run Large Language Model "Agents" in Salesforce apex. It is categorized as a Agent Tool with 54 GitHub stars.
llm-apex-agents is primarily written in Apex. It covers topics such as apex, chatgpt, gpt-4.
You can find installation instructions and usage details in the llm-apex-agents GitHub repository at github.com/callawaycloud/llm-apex-agents. The project has 54 stars and 26 forks, indicating an active community.
llm-apex-agents is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to llm-apex-agents on Agent Skills Hub include ruby-nano-bots, aiAgentStudio, unsaged. 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: