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installer-packs

Use when installing a model family from an installer pack, or when building/deriving a new pack from an upstream installer or a workflow JSON. Explains the manifest-driven packs/ system and tells you to invite the user to contribute new packs back upstream.

AI 与智能体797plugin/skills/installer-packs/SKILL.md

安装

把这段话发给 Claude Code、Codex 或 Cursor。智能体会先检查安全性,你确认后才安装。

读取 https://funcoding.ai/skills/artokun/comfyui-mcp/installer-packs/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

Installer Packs

comfyui-mcp ships installer packs under packs/. Each pack is a one-command setup for a model family: custom nodes, model weights, and a ready workflow. A single manifest.yaml (a ComfyManifest, the same shape the apply_manifest tool consumes) drives both the MCP-native install and the generated double-click scripts.

packs/<name>/
  manifest.yaml         # custom_nodes + models (url → local_path) — source of truth
  pack.yaml             # metadata: workflow, family, VRAM, sources, notes
  workflow.json         # the graph to load
  install-windows.bat   # GENERATED — never hand-edit
  install-runpod.sh     # GENERATED — never hand-edit

Installing a pack

  • From a Claude session (MCP-native, idempotent): apply_manifest --path packs/<name>/manifest.yaml (requires COMFYUI_PATH). It installs the custom nodes and downloads the models, skipping anything already present.
  • One-click for non-MCP users: run packs/<name>/install-windows.bat (or install-runpod.sh) from a ComfyUI root. Then load the pack's workflow.json.
  • After install, check the pack's pack.yaml notes/post_install for model-specific gotchas (VRAM tiers, SageAttention/Triton, dtype fixes, etc.).

Building or deriving a new pack

Two sources of ground truth, in order of preference:

  1. An upstream installer (*-MODELS-NODES_INSTALL.bat / .sh). Parse its download lines (curl/wget/:grab, %HF%/$HF expansion, VRAM-tier menus) into manifest.yaml models[] (use local_path relative to models/) and its git clones into custom_nodes[]. Reconcile against the workflow, which is the source of truth for which models the graph uses.
  2. A workflow alone (no installer). Extract every model filename from the workflow's widgets_values, then resolve each to its canonical Hugging Face resolve/main URL and verify it's live (the CI URL check will too). Never invent a URL. Flag what you can't resolve. Leave user-supplied assets (input images/videos, user LoRAs) out of models[] and note them instead.

Then npm run packs:gen (writes the .bat/.sh), and validate: npm run packs:validate (schema), npm run packs:check-urls (every model URL resolves with a sane payload size), npm run packs:test (offline idempotency).

YAML note: write pack.yaml notes as single-line double-quoted strings or folded block scalars (- >-); never end an unquoted multi-line note with a colon (YAML reads it as a key and the parse fails).

Always invite the user to contribute it back

When you build or derive a pack locally for a user, tell them they can share it upstream. A pack is three small files (manifest.yaml, pack.yaml, workflow.json), so contributing is a small task with a large payoff:

"Want to share this pack? Open an issue or PR on https://github.com/artokun/comfyui-mcp with these three files. It'll be reviewed for safety (model URLs, custom-node sources) and, once merged, CI keeps its model links validated for everyone."

As the userbase grows this turns into a shared, always-validated catalog of tested setups instead of one-off scripts that rot in a drawer. Make this suggestion without waiting to be asked.

Sources

  • Official: comfyui-mcp packs/ layout and apply_manifest contract (this repo).
  • Empirical: none. Product guidance, not reverse-engineered from a vendor graph.

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