by smkrv · Claude Skill · ★ 83
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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 | 83 |
| Forks | 7 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 65/100 |
| Last Updated | 2026-10-13 |
| Created | 2024-11-14 |
| Platforms | claude-code, python |
| Est. Tokens | ~19k |
🤖 HA Text AI for Home Assistant Advanced AI Integration for Home Assistant with LLM multi-provider support <
These tools work well together with ha-text-ai for enhanced workflows:
Looking for a ha-text-ai alternative? If you're comparing ha-text-ai with other claude skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Control and query Home Assistant from Claude and other LLMs — a Model Context Protocol (MCP) server.
Exposes internet search tools for use by LLM-backed Assist in Home Assistant
Python library for building with LLMs. One interface across 11 providers (OpenAI, Anthropic, Gemini, DeepSeek,
Custom node for ComfyUI/Stable Diffustion
Ask your house a question, get a number back. Home Assistant integration for TypeSafe Jev: typed answers as se
Use machine learning to make your institutional communication more understandable and inclusive.
Explore other popular claude skill 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: