# Tools

> Every listed resource, editors’ picks first. The filters below can be combined.

- Search: append `?q=<keywords>` 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=<cli|skill|plugin|mcp>` to the URL.
- Filter by profession: append `?profession=<profession id>` 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=<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 `obsidian`, `knowledge-base`: 5 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.

- [Claude Scholar](https://hebbmind.com/skill/claude-scholar.md): [Skill] Semi-automated research workflow for computer science and AI researchers: ideation, Zotero literature management, experiment analysis and reports, paper writing and polishing, and rebuttals, with optional Obsidian knowledge base. 40+ skills; also installable as a Claude Code plugin.
- [Claude Scholar](https://hebbmind.com/plugin/claude-scholar.md): [Plugin] Semi-automated research assistant for CS and AI researchers that links ideation, Zotero literature management, experiment analysis and reporting, paper writing and reviewer responses, and keeps project knowledge in Obsidian. Branches for Codex and other agents exist.
- [Basic Memory](https://hebbmind.com/mcp/basic-memory.md): [MCP] Stores agent memory as local Markdown notes that both people and AI can read, write, search and link, and you can open them directly in Obsidian. Local-first, open source and free, with a paid cloud sync option.
- [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.
