Repository
ddalcu/mlx-serve agent skills
- skills
- 4
- GitHub stars
- 1.8k
GitHub description: “Native LLM inference server for Apple Silicon. OpenAI + Anthropic API compatible. No Python. Zig backend, Swift frontend macOS app with chat, music, voice, video generation.”
- Stars
- 1,806 (180 forks)
- Licence
- Unknown
- Last push
- Oct 2026
- Created
- Feb 2026
- Homepage
- mlxserve.com
- agent
- anthropic-api
- apple-silicon
- claude-code
- inference
- llm
- local-llm
- macos
- macos-app
- mlx
- openai-api
- tool-calling
- zig
- deepseek-v4
- diffusion
- image-generation
Install all skills
npx skills add ddalcu/mlx-serveAdd --skill <name> for a single skill and -a <agent> to choose the agent (see the agent guides).
Skills in ddalcu/mlx-serve, ranked
Ranked by score. Sort bymost stars,trending,newest,recently updated
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Hook an app, game or script up to the local mlx-serve server for LLM chat, embeddings, image, speech, music, sound effect, video and 3D generation, and Laya/Kev/Clef typed decisions. | ddalcu/ | 1.8k | — | ~1k | Automated safety check: Pass | Unknown | today |
| 2 | 2.Release mlx-serve pre-release validation checklist, CalVer versioning, release steps, and CHANGELOG style. | ddalcu/ | 1.8k | — | ~1.8k | Automated safety check: Pass | Unknown | today |
| 3 | 3.Bench mlx-serve benchmarking methodology — bench.sh/llmprobe usage, comparison-trap rules (same-methodology cells only, spec-decode variance, thermal lies, engine naming), perf-claim etiquette. | ddalcu/ | 1.8k | 1 repo | ~1.1k | Automated safety check: Pass | Unknown | today |
| 4 | Turn llmprobe reports into the charts a perf PR embeds (one line per arm across context size, every point labelled, machine and model in the caption) and host them so the PR body renders them. | ddalcu/ | 1.8k | — | ~594 | Automated safety check: Pass | Unknown | today |
Questions, answered from the data.
What is the best skill in ddalcu/mlx-serve?
Mlx Serve from ddalcu/mlx-serve ranks first of the 4 skills in ddalcu/mlx-serve listed here, with the highest score: its repository has 1.8k GitHub stars, its SKILL.md loads about 1k tokens and it passes the automated safety check with no findings. Next come Release and Bench.
Are the skills in ddalcu/mlx-serve official?
None yet. All 4 skills in ddalcu/mlx-serve listed here come from community repositories; a skill counts as official when the product's own GitHub organization publishes it.
How do I install all skills from ddalcu/mlx-serve?
Run npx skills add ddalcu/mlx-serve in your project: the open-source skills CLI installs the repository's skills into your coding agent's skills folder. To install a single skill, open its page here for the exact command.
How are these skills ranked?
By Skill Navigator score, which combines the GitHub stars of the skill's repository (shared across that repo's skills and discounted for large collections), how many other GitHub owners carry a copy of the skill, and automated SKILL.md quality checks, minus penalties for safety-check warnings and for each further skill from the same repository. Skills that fail the safety check are not listed.