# Tools > Every listed resource, editors’ picks first. The filters below can be combined. - Search: append `?q=` to the URL. Separate several keywords with spaces; all of them must match. Matches name, repository, tags, professions, description and README. - Filter by type: append `?type=` to the URL. - Filter by profession: append `?profession=` to the URL. Separate several ids with commas; a resource matches when it suits any of them. Ids are listed at https://hebbmind.com/api/v1/professions - Filter by tag: append `?tag=` to the URL. Separate several tags with commas; a resource must carry all of them. Tags are listed at https://hebbmind.com/api/v1/tags Resources for Full-stack / Indie or ML / AI, Tagged `knowledge-base`, `pdf`: 3 items. > - Full-stack / Indie: General software work: coding-agent workflows, code review, debugging and Git collaboration. > - ML / AI: Model training, evaluation and LLM application development. - [book-to-skill](https://hebbmind.com/skill/book-to-skill.md): [Skill] Distills technical books, doc folders or paper collections (PDF, EPUB, DOCX, Markdown and more) into an agent skill with a core framework, on-demand chapter files, glossary and cheat sheet for lookup while working. Extraction needs local Python; poppler or docling optional for PDFs. - [evil-read-arxiv](https://hebbmind.com/skill/evil-read-arxiv.md): [Skill] Recommends daily papers from arXiv and Semantic Scholar by research interest, reads them and writes illustrated Obsidian notes and a paper graph; can also search venues like CVPR and NeurIPS. Needs Python 3, Obsidian, a vault path and an interests config; the web app needs an Anthropic API key. - [dailypaper-skills](https://hebbmind.com/skill/dailypaper-skills.md): [Skill] Pulls new papers from Hugging Face Daily Papers and arXiv, scores them by research area into a recommendation page, and writes deep-read Obsidian notes for key ones; can also batch-read Zotero collections. Needs Python 3, Obsidian and poppler; copy the whole skills folder per the README.