llmfit-advisor
Detect local hardware (RAM, CPU, GPU/VRAM) and recommend the best-fit local LLM models with optimal quantization, speed estimates, and fit scoring.
npx skills add AlexsJones/llmfit --skill llmfit-advisor --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# llmfit-advisor Hardware-aware local LLM advisor. Detects your system specs (RAM, CPU, GPU/VRAM) and recommends models that actually fit, with optimal quantization and speed estimates. ## When to use (trigger phrases) Use this skill immediately when the user asks any of: - "what local models can I run?" - "which LLMs fit my hardware?" - "recommend a local model" - "what's the best model for my GPU?" - "can I run Llama 70B locally?" - "configure local models" - "set up Ollama models" - "what models fit my VRAM?" - "help me pick a local model for coding" Also use this skill when: - The user wants to configure `models.providers.ollama` or `models.providers.lmstudio` - The user mentions running models locally and you need to know what fits - A model recommendation is needed and the user has local inference capability (Ollama, vLLM, LM Studio) ## Quick start ### Detect hardware ```bash llmfit --json system ``` Returns JSON with CPU, RAM, GPU name, VRAM, multi-GPU info, and whether memory is unified (Apple Silicon). ### Get top recommendations ```bash llmfit recommend --json --limit 5 ``` Returns the top 5 models ranked by a composite score (quality, speed, fit, context) with optimal qu
- When to use (trigger phrases)
- Quick start
- Detect hardware
- Get top recommendations
- Filter by use case
- Filter by minimum fit level
- Understanding the output
- System JSON
- Recommendation JSON
- Fit levels explained
- Run modes explained
- Configuring OpenClaw with results
- For Ollama
- For vLLM / LM Studio
llmfit --json system llmfit recommend --json --limit 5 llmfit recommend --json --use-case coding --limit 3 llmfit recommend --json --use-case reasoning --limit 3 llmfit recommend --json --use-case chat --limit 3 llmfit recommend --json --min-fit good --limit 10
What does the llmfit-advisor skill do?
Detect local hardware (RAM, CPU, GPU/VRAM) and recommend the best-fit local LLM models with optimal quantization, speed estimates, and fit scoring.
How do I install it?
Run `npx skills add AlexsJones/llmfit --skill llmfit-advisor --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From AlexsJones/llmfit, a repository with 31,120 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.