# 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 DevOps / SRE or ML / AI, Tagged `ollama`: 2 items.

> - Full-stack / Indie: General software work: coding-agent workflows, code review, debugging and Git collaboration.
> - DevOps / SRE: Deployment, monitoring, cloud resources and reliability.
> - ML / AI: Model training, evaluation and LLM application development.

- [Ollama](https://hebbmind.com/cli/ollama.md): [CLI] Download and run open models such as Gemma locally with one command. Provides a REST API and Python/JS libraries, and ollama launch can point Claude Code, Codex and other agents at local models.
- [llmfit](https://hebbmind.com/cli/llmfit.md): [CLI] Detects your CPU, memory and GPU and scores open models on whether they run, speed, quality and context, then works with local runtimes like Ollama, llama.cpp and MLX to download and benchmark them. recommend --json gives agent-friendly output.