* 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)
3.8 KiB
Example Workflows
These are starter API-format workflows for the most common tasks. They're
ready to run with scripts/run_workflow.py once you've installed (or have
cloud access to) the listed models.
| File | Purpose | Required models | Min VRAM |
|---|---|---|---|
sd15_txt2img.json |
SD 1.5 text-to-image (512×512) | SD1.5 checkpoint, e.g. v1-5-pruned-emaonly.safetensors |
4 GB |
sdxl_txt2img.json |
SDXL text-to-image (1024×1024) | sd_xl_base_1.0.safetensors |
8 GB |
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) |
sdxl_img2img.json |
SDXL image-to-image | SDXL checkpoint | 8 GB |
sdxl_inpaint.json |
SDXL inpainting (image + mask) | SDXL checkpoint | 8 GB |
upscale_4x.json |
Standalone 4× ESRGAN upscale | 4x-UltraSharp.pth (or any upscaler) |
4 GB |
animatediff_video.json |
AnimateDiff text-to-video (16 frames) | SD1.5 checkpoint, mm_sd_v15_v2.ckpt motion module |
8 GB |
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 |
Quick start
# Run a workflow with prompt injection
python3 ../scripts/run_workflow.py \
--workflow sdxl_txt2img.json \
--args '{"prompt": "majestic eagle in flight", "seed": 12345, "steps": 35}' \
--output-dir ./out
# Img2img: upload an input image first via the script's helper
python3 ../scripts/run_workflow.py \
--workflow sdxl_img2img.json \
--input-image image=./photo.png \
--args '{"prompt": "make it watercolor", "denoise": 0.6}' \
--output-dir ./out
# Cloud (set API key once)
export COMFY_CLOUD_API_KEY="comfyui-..."
python3 ../scripts/run_workflow.py \
--workflow flux_dev_txt2img.json \
--args '{"prompt": "a fox in a misty forest"}' \
--host https://cloud.comfy.org \
--output-dir ./out
# What can I tweak in this workflow?
python3 ../scripts/extract_schema.py sdxl_txt2img.json --summary-only
# Are all required models / nodes installed?
python3 ../scripts/check_deps.py wan_video_t2v.json
Notes
-
Inpaint masks: white pixels = "regenerate this region", black = preserve. ComfyUI's
LoadImageMaskreads the red channel by default; export your mask as a single-channel image or as a normal RGB where red==intensity. -
Denoise strength in img2img:
0.0= output identical to input,1.0= ignore input entirely. Sweet spot is usually 0.4–0.7. -
Flux Dev needs ~24 GB VRAM in its base form. The
flux1-dev-fp8.safetensorsvariant (already on Comfy Cloud) cuts that roughly in half. -
Video workflows can take many minutes. The skill auto-detects video output nodes and bumps the default timeout to 900s. Override with
--timeout 1800. -
These JSON files are deliberately API format (top-level keys are node IDs with
class_type), not editor format. To open them in ComfyUI's web UI for visual editing, useWorkflow → Load (API Format)orWorkflow → Openand follow the prompt.
Cloud vs local model names
Comfy Cloud's preinstalled checkpoints sometimes have a -fp16 suffix
(v1-5-pruned-emaonly-fp16.safetensors) while the canonical local download
keeps the original name (v1-5-pruned-emaonly.safetensors). The example
workflows use the local-canonical names. When running on cloud, override with:
python3 ../scripts/run_workflow.py \
--workflow sd15_txt2img.json \
--args '{"ckpt_name": "v1-5-pruned-emaonly-fp16.safetensors", "prompt": "..."}' \
--host https://cloud.comfy.org
The ckpt_name, vae_name, lora_name, unet_name, etc. are all exposed
as controllable parameters by extract_schema.py — discover what's installed
with comfy model list (local) or curl /api/experiment/models/checkpoints
(cloud).