# earthtojake/text-to-cad > A library of agent skills that generate, inspect, and prepare CAD models, drawings, and robot description files (URDF, SRDF, SDF) from text requests. - Magnitude: 3.8 out of 10 — Steady - Stars: 23,949 total · +72 stars measured 2026-10-29, 00:04–05:43 UTC, ≈ 290 by evening - Star trust: star growth looks organic - Category: AI agents · Language: Python · License: MIT · Created: 2026-04-22 · Last push: 2026-10-29 - GitHub: https://github.com/earthtojake/text-to-cad · Homepage: https://www.texttocad.dev · Page: https://gitnova.dev/en/r/earthtojake/text-to-cad ## Useful for - Create a STEP model from a text description and export it to STL - Generate a robot URDF with links, joints, and inertial parameters - Validate a DXF or STEP file before uploading to SendCutSend ## Why it’s here - Star-counter measurements on 2026-10-29 (UTC), 00:04–05:43: 23877 → 23949 stars (+72). This is the change over that interval. - Estimated end-of-day forecast: about +289 stars, using observed gains and the previous day. - GitHub Trending this month: #4, +7,453 stars. - About 19 forks a day — people are taking the code. ## Star trust Star growth looks organic. Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer. ## Numbers - Forks: 2,308 - Issues and pull requests: 716 - Watchers: 103 - Average over the last week: 236 per day - Usual pace: 264 per day - Stars in the last hour (measured): 10 - Latest release: v0.8.2 (2026-10-28) ## Stars per day, last 30 days (oldest → newest, today is partial) 2026-09-30 … 2026-10-29: 25, 27, 36, 80, 363, 574, 549, 209, 231, 289, 218, 355, 351, 351, 390, 308, 290, 247, 214, 290, 270, 297, 238, 207, 182, 202, 211, 277, 286, 72 ## Magnitude by day, last 14 days 10-16 4.0, 10-17 4.0, 10-18 3.9, 10-19 3.9, 10-20 3.8, 10-21 3.8, 10-22 4.0, 10-23 3.8, 10-24 3.6, 10-25 3.4, 10-26 3.4, 10-27 3.6, 10-28 3.9, 10-29 3.8 ## Spotted in now - GitHub Trending this month: #4, +7,453 stars ## More in this category 1. **HKUDS/DeepTutor** — 8.8 · Breakout · AI agents · Python · +521 stars measured 2026-10-29, 00:02–05:41 UTC, ≈ 1,996 by evening A lifelong personalized AI tutor with long-term memory: builds learning paths, reads documents and books, and runs practice and assessments via a multi-agent system and RAG. Full card: https://gitnova.dev/en/r/HKUDS/DeepTutor.md 2. **elayadesign/ai-design-skills** — 7.9 · Breakout · AI agents · +284 stars measured 2026-10-29, 00:02–05:41 UTC, ≈ 1,293 by evening A collection of markdown-based design skills for AI coding tools like Claude Code, Cursor, Codex and Windsurf, covering landing page design and turning static designs into animated showcases. Full card: https://gitnova.dev/en/r/elayadesign/ai-design-skills.md 3. **pbakaus/impeccable** — 7.7 · Breakout · AI agents · Rust · +704 stars measured 2026-10-29, 00:02–05:41 UTC, ≈ 2,588 by evening A set of commands and detector rules for AI coding agents that helps them produce better frontend design instead of generic templates. Installs as a skill into Claude Code, Cursor, Codex and other harnesses. Full card: https://gitnova.dev/en/r/pbakaus/impeccable.md 4. **anonnerdfrenzy/survival-llm** — 7.7 · Early signal · AI agents · Python · +60 stars measured 2026-10-29, 00:02–05:41 UTC, ≈ 350 by evening A local offline LLM assistant with a library of ~1.5M survival, medical and how-to articles; every answer cites the exact source passage. Full card: https://gitnova.dev/en/r/anonnerdfrenzy/survival-llm.md 5. **unclebob/ub-mode** — 7.6 · Breakout · AI agents · +236 stars measured 2026-10-29, 00:02–05:41 UTC, ≈ 1,087 by evening An agent skill that enforces disciplined software engineering practices when writing or changing code: TDD, root-cause fixes, behavior testing, and quality gates via mutation testing. Installed as SKILL.md into the agent's skills directory. Full card: https://gitnova.dev/en/r/unclebob/ub-mode.md --- Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score. Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast. Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself. Data as of 2026-10-29 05:52 UTC, updated every 30 minutes.