c49fa88b80
* refactor(skills): shipped-set slim — 15 skills to optional, github six-way merge, pdf absorbs OCR+nano-pdf, channel-gated teams pipeline
Maintainer-directed shipped-skills curation (skills index 1,900 -> ~1,400
tok/call on desktop; every session pays the index, so this is a per-call
diet on all installs):
- optional-skills moves (installable via skills hub, history preserved):
creative comfyui/ascii-art/excalidraw/pretext/sketch/touchdesigner-mcp;
ALL of mlops (huggingface-hub, llama-cpp, serving-llms-vllm,
weights-and-biases, evaluating-llms-harness — subcategory structure
kept); research-paper-writing (55 supporting files, 17.3K-tok load);
openhue; blogwatcher (first taught the cronjob monitor-field watch
pattern + web_extract instead of pre-cron manual workflows)
- DELETED session-librarian (Aug-12 'inspired by Perplexity Computer'
port, never maintainer-intended; session_search covers discovery)
- github: six skills (auth, issues, pr-workflow, issue-to-pr,
code-review, repo-management) merged into ONE software-development/
github skill — routing body + complete per-workflow references;
benbarclay authorship credited; codebase-inspection rides along;
discipline pins from test_github_issue_to_pr_skill.py preserved
against the reference body in the new test_github_skill.py
- pdf absorbs ocr-and-documents + nano-pdf as references/ + scripts
(extract_pymupdf, extract_marker converted to the argparse house
standard its contract test enforces)
- NEW session_platforms frontmatter gate (metadata.hermes): hides a
skill from the index on gateway channels it is not for; fail-open on
unknown platform; teams-meeting-pipeline gated to [teams, cron]
- blocked-page-recovery: research -> new web category; trigger-first
description ('Use when a fetch fails: 403/429, paywall, WAF, bot
wall.') so the model actually reaches for it on blocked fetches
- docs regenerated via generate-skill-docs.py (195 pages); related_skills
swept repo-wide; tests: 1672 passed (2 openclaw failures pre-existing
on clean main, Windows-local)
* chore: ignore .skills_prompt_snapshot.json (local index cache, accidentally committed)
87 lines
3.8 KiB
Markdown
87 lines
3.8 KiB
Markdown
# Example Workflows
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These are starter API-format workflows for the most common tasks. They're
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ready to run with `scripts/run_workflow.py` once you've installed (or have
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cloud access to) the listed models.
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| File | Purpose | Required models | Min VRAM |
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|------|---------|-----------------|----------|
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| `sd15_txt2img.json` | SD 1.5 text-to-image (512×512) | SD1.5 checkpoint, e.g. `v1-5-pruned-emaonly.safetensors` | 4 GB |
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| `sdxl_txt2img.json` | SDXL text-to-image (1024×1024) | `sd_xl_base_1.0.safetensors` | 8 GB |
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| `flux_dev_txt2img.json` | Flux Dev text-to-image (1024×1024) | `flux1-dev.safetensors`, `t5xxl_fp16.safetensors`, `clip_l.safetensors`, `ae.safetensors` | 24 GB (or use `flux1-dev-fp8`) |
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| `sdxl_img2img.json` | SDXL image-to-image | SDXL checkpoint | 8 GB |
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| `sdxl_inpaint.json` | SDXL inpainting (image + mask) | SDXL checkpoint | 8 GB |
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| `upscale_4x.json` | Standalone 4× ESRGAN upscale | `4x-UltraSharp.pth` (or any upscaler) | 4 GB |
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| `animatediff_video.json` | AnimateDiff text-to-video (16 frames) | SD1.5 checkpoint, `mm_sd_v15_v2.ckpt` motion module | 8 GB |
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| `wan_video_t2v.json` | Wan 2.x text-to-video (~33 frames) | `wan2.2_t2v_1.3B_fp16.safetensors`, `umt5_xxl_fp16.safetensors`, `wan_2.1_vae.safetensors` | 24 GB |
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## Quick start
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```bash
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# Run a workflow with prompt injection
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python3 ../scripts/run_workflow.py \
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--workflow sdxl_txt2img.json \
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--args '{"prompt": "majestic eagle in flight", "seed": 12345, "steps": 35}' \
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--output-dir ./out
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# Img2img: upload an input image first via the script's helper
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python3 ../scripts/run_workflow.py \
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--workflow sdxl_img2img.json \
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--input-image image=./photo.png \
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--args '{"prompt": "make it watercolor", "denoise": 0.6}' \
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--output-dir ./out
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# Cloud (set API key once)
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export COMFY_CLOUD_API_KEY="comfyui-..."
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python3 ../scripts/run_workflow.py \
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--workflow flux_dev_txt2img.json \
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--args '{"prompt": "a fox in a misty forest"}' \
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--host https://cloud.comfy.org \
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--output-dir ./out
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# What can I tweak in this workflow?
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python3 ../scripts/extract_schema.py sdxl_txt2img.json --summary-only
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# Are all required models / nodes installed?
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python3 ../scripts/check_deps.py wan_video_t2v.json
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```
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## Notes
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- **Inpaint masks**: white pixels = "regenerate this region", black = preserve.
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ComfyUI's `LoadImageMask` reads the **red channel** by default; export your
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mask as a single-channel image or as a normal RGB where red==intensity.
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- **Denoise strength** in img2img: `0.0` = output identical to input,
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`1.0` = ignore input entirely. Sweet spot is usually 0.4–0.7.
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- **Flux Dev** needs ~24 GB VRAM in its base form. The `flux1-dev-fp8.safetensors`
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variant (already on Comfy Cloud) cuts that roughly in half.
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- **Video workflows** can take many minutes. The skill auto-detects video
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output nodes and bumps the default timeout to 900s. Override with `--timeout 1800`.
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- These JSON files are deliberately **API format** (top-level keys are node IDs
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with `class_type`), not editor format. To open them in ComfyUI's web UI for
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visual editing, use `Workflow → Load (API Format)` or `Workflow → Open` and
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follow the prompt.
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## Cloud vs local model names
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Comfy Cloud's preinstalled checkpoints sometimes have a `-fp16` suffix
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(`v1-5-pruned-emaonly-fp16.safetensors`) while the canonical local download
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keeps the original name (`v1-5-pruned-emaonly.safetensors`). The example
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workflows use the local-canonical names. When running on cloud, override with:
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```bash
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python3 ../scripts/run_workflow.py \
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--workflow sd15_txt2img.json \
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--args '{"ckpt_name": "v1-5-pruned-emaonly-fp16.safetensors", "prompt": "..."}' \
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--host https://cloud.comfy.org
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```
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The `ckpt_name`, `vae_name`, `lora_name`, `unet_name`, etc. are all exposed
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as controllable parameters by `extract_schema.py` — discover what's installed
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with `comfy model list` (local) or `curl /api/experiment/models/checkpoints`
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(cloud).
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