by benavlabs · Agent Tool · ★ 70
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
pip install "clientai[all]"
pip install "clientai[openai]" # For OpenAI supportTaken from the project's README on GitHub.
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.
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 | 70 |
| Forks | 7 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 71/100 |
| Open Issues | 12 |
| Last Updated | 2025-07-06 |
| Created | 2024-10-02 |
| Platforms | cli, python |
| Est. Tokens | ~265k |
ClientAI A unified client for AI providers with built-in agent support. ClientAI is a Python package that provides a unified framework for building AI applications, from direct provider interactions to transparent LLM-powered agents, with seamless support for OpenAI, Replicate, Groq and Ollama.
These tools work well together with clientai for enhanced workflows:
Looking for a clientai alternative? If you're comparing clientai 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.
This MCP server provides documentation about Strands Agents to your GenAI tools, so you can use your favorite
[archived] c4 GenAI Suite
A curated list of tools, papers, and datasets for applying AI to cybersecurity tasks. This list primarily focu
Python client library for improving your LLM app accuracy
◉ Universal Intelligence: AI made simple.
Curiso is an infinite canvas for your thoughts
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: