by hschickdevs · Agent Tool · ★ 7
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. 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 | 7 |
| Forks | 1 |
| Language | Python |
| Category | Agent Tool |
| License | GPL-3.0 |
| Quality Score | 68/100 |
| Last Updated | 2024-12-09 |
| Created | 2024-03-07 |
| Platforms | python |
| Est. Tokens | ~15k |
Telegram bot that uses AI to generate full codebases from user prompts, providing structured, ready-to-deploy software projects, differentiating from simple code generation by offering entire architectural solutions.
Looking for a Telegram-AI-Software-Architect alternative? If you're comparing Telegram-AI-Software-Architect 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.
A seamless integration of Chainlit with LangGraph. Ideal for fast prototyping multi-LLM chatbot or AI agents.
Home Assistant add-on: Claude Code, OpenAI/GPT, Gemini
Your Digital Companion. Self-hosted Telegram bot orchestrating multiple AI providers (OpenAI, Anthropic, Googl
🤖 A curated list of websites that restrict access to AI Agents, AI crawlers and GPTs
Self-hosted AI assistant built on DeepAgents, LangChain and LangGraph: Telegram chat, scheduled tasks, MCP int
A memory-first AI agent that remembers why decisions were made — not just the last message. Runs local (Ollama
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: