by Maximilian-Winter · Agent Tool · ★ 658
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
pip install llama-cpp-agent
Taken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 658 |
| Forks | 74 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 72/100 |
| Open Issues | 25 |
| Last Updated | 2026-03-09 |
| Created | 2023-12-29 |
| Platforms | python |
| Est. Tokens | ~383k |
llama-cpp-agent Not Longer Maintained. Use instead ToolAgents or other Python agentic frameworks. [] Introduction The llama-cpp-agent framework is a tool designed to simplify interactions with Large Language Models (LLMs).
These tools work well together with llama-cpp-agent for enhanced workflows:
Looking for a llama-cpp-agent alternative? If you're comparing llama-cpp-agent with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
[ICML 2024] LLMCompiler: An LLM Compiler for Parallel Function Calling
A curated list of tools, papers, and datasets for applying AI to cybersecurity tasks. This list primarily focu
Official Repo for ICML 2024 paper "Executable Code Actions Elicit Better LLM Agents" by Xingyao Wang, Yangyi C
[GenAI Application Development Framework] 🚀 Build GenAI application quick and easy 💬 Easy to interact with
Low code tool to rapidly build and coordinate multi-agent teams
历年ICLR论文和开源项目合集,包含ICLR2021、ICLR2022、ICLR2023、ICLR2024、ICLR2025.
Explore other popular agent tool tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: