# 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

Tagged `llama-cpp`: 2 items.

- [llama.cpp](https://hebbmind.com/es/cli/llama-cpp.md): [CLI] Local LLM inference engine in plain C/C++ with a command-line chat and an OpenAI-compatible HTTP server; pulls and runs GGUF models straight from Hugging Face. Supports Apple Silicon, CUDA, Vulkan and other hardware, plus low-bit quantization.
- [llmfit](https://hebbmind.com/es/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.