load-preset
The vllm-on-tap preset - its format, where a preset name resolves (custom in .vot/presets/, then builtin in the official repository), how it is validated and…
Skill by using-system
Chalk Labs
Need help deploying load-preset?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/using-system-load-preset
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/load-preset
What's inside
- Skill name
load-preset- Description
- The vllm-on-tap preset - its format, where a preset name resolves (custom in .vot/presets/, then builtin in the official repository), how it is validated and how its per-stack overrides merge. Read when a preset is served, listed, written or checked.
- License
- MIT
- Instructions
- 65 lines in SKILL.md · view on GitHub
Before installing
- Instructions call the network
Files (1)
- SKILL.md
SKILL.md (first lines)
# load-preset A preset states what vLLM serves - never where or how it is hosted (no image, region, port or resource name). ## Format The contract is `presets/schema.json` in the official repository (`https://raw.githubusercontent.com/using-system/vllm-on-tap/main/presets/schema.json`). | Field | Required | Meaning | |---|---|---| | `name` | yes | the preset's name, equal to the file name without `.yaml` | | `description` | no | one line | | `model` | yes | Hugging Face repository id vLLM serves | | `served_model_name` | no | the OpenAI API `model` name clients send; defaults to `name` | | `gpu_memory_gb` | no | the smallest GPU memory the preset runs on | | `vllm_args` | no | flags passed as-is to `vllm serve`, one per key (`--flag: value`); `true` is a bare flag, `false` omits it | | `env` | no | names of environment variables the preset needs (`HF_TOKEN` for a gated model) | | `stacks.<stack type>` | no | overrides of `model`, `vllm_args` (merged key by key) and `gpu_memory_gb` for one stack type (the override under a stack type's earlier name, per the stack-guide skill, is read as its current name's) | ## Resolve For a preset name `<name>`, in order: 1. `.vot/presets/<name>.yaml` in the user's repository - a custom preset, which shadows a builtin of the same name. 2. `https://raw.githubusercontent.com/using-system/vllm-on-tap/main/presets/<name>.yaml` (`curl -fsSL <url>`); a 404 means no builtin of that name. Found in neither: list the available presets (the files in `.vot/presets/` and the *Builtin presets* below) and stop. ## Validate Validate the resolved file before use: ```bash uvx check-jsonschema --schemafile https://raw.githubusercontent.com/using-system/vllm-on-tap/main/presets/schema.json <preset file> ``` A builtin fetched over HTTP is first saved to `.vot/run/<name>.yaml`. Any error: show it and stop - a preset that fails its schema is never served. Also refuse a `name` that differs from the file name. ## Merge The override of a stack type with an earlier name (the stack-guide skill) is `stacks.<current name>`, or `stacks.<earlier name>` when it is absent. After validation, when the preset has `stacks.<current stack type>`: its `model` and `gpu_memory_gb` replace the preset's; its `vllm_args` are merged key by key into the preset's (the override wins). `served_model_name` defaults to `name` when absent. ## Builtin presets | Name | Model | GPU memory | |---|---|---| | `gemma4-12b-qat` | `google/gemma-4-12B-it-qat-w4a16-ct` - NVIDIA stacks only, not `local-vllm-metal` | 16 GB | | `gemma4-e4b-qat` | `google/gemma-4-E4B-it-qat-w4a16-ct` (MLX `mlx-community/gemma-4-e4b-it-4bit` on `local-vllm-metal`) | 16 GB | | `gemma4-e2b-qat` | `google/gemma-4-E2B-it-qat-w4a16-ct` (MLX `mlx-community/gemma-4-e2b-it-4bit` on `local-vllm-metal`) | 16 GB | | `qwen38-27b-agentic` | `Qwen/Qwen3.8-27B` (MLX `mlx-community/Qwen3.8-27B-4bit` on `local-vllm-metal`) - not yet verified live | 80 GB (48 GB on `local-vllm-metal`) |
From using-system/vllm-on-tap, MIT.
More from using-system/vllm-on-tap
- 0.589score
stack-guide
using-system
How vllm-on-tap runs vLLM on each stack type, supported or planned - one reference per type with its prerequisites, config fields, serve, readiness, destroy…
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
vot-config
using-system
Create, update or select a vllm-on-tap environment - its stack type, its config and its optional OTLP traces endpoint - checking and offering to install the…
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
vot-serve
using-system
Serve a vLLM preset on the current vllm-on-tap environment - resolve the preset (custom or builtin), start vLLM on the environment's stack as unit…
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
vllm-guide
using-system
vLLM capabilities a vllm-on-tap preset or serve needs - the serve flags, tracing over OTLP, the API key, the OpenAI-compatible API and tuning for a GPU - each…
SkillAFreshness: A★ 1Claude Code +9 - 0.582score
vot-instrument-preset
using-system
Create or edit a vllm-on-tap custom preset in .vot/presets/ from a free-form request - a model of interest, a Hugging Face link, a GPU, a constraint.
SkillAFreshness: A★ 1Claude Code +9 - 0.582score
vot-destroy
using-system
Destroy the unit vot-<preset> a vllm-on-tap serve created on the current environment (a process, a container or a cloud app), keeping the environment itself.
SkillAFreshness: A★ 1Claude Code +9
Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Sep 27, 2026 (1 month ago)
- Last release
- Sep 27, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/using-system/vllm-on-tap
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from using-system
- 0.589score
stack-guide
using-system
How vllm-on-tap runs vLLM on each stack type, supported or planned - one reference per type with its prerequisites, config fields, serve, readiness, destroy…
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
vot-config
using-system
Create, update or select a vllm-on-tap environment - its stack type, its config and its optional OTLP traces endpoint - checking and offering to install the…
SkillAFreshness: A★ 1Claude Code +9 - 0.587score
vot-serve
using-system
Serve a vLLM preset on the current vllm-on-tap environment - resolve the preset (custom or builtin), start vLLM on the environment's stack as unit…
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
vllm-guide
using-system
vLLM capabilities a vllm-on-tap preset or serve needs - the serve flags, tracing over OTLP, the API key, the OpenAI-compatible API and tuning for a GPU - each…
SkillAFreshness: A★ 1Claude Code +9 - 0.582score
vot-instrument-preset
using-system
Create or edit a vllm-on-tap custom preset in .vot/presets/ from a free-form request - a model of interest, a Hugging Face link, a GPU, a constraint.
SkillAFreshness: A★ 1Claude Code +9 - 0.582score
vot-destroy
using-system
Destroy the unit vot-<preset> a vllm-on-tap serve created on the current environment (a process, a container or a cloud app), keeping the environment itself.
SkillAFreshness: A★ 1Claude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get load-preset running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
load-preset skill. Agent Mart. https://agentmart.dev/skills/using-system-load-preset (last updated 2026-10-24)