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Skill

/color-correction

Diagnose and fix video/image color OBJECTIVELY with the get_image (action:"analyze_color") tool (scopes/stats such as black/white points, contrast, saturation, clipping, cast) instead of eyeballing a contact sheet. Covers the "washed out" signature, why reference color-match

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comfyui-mcp
74242 skills4 agents11 commands1 MCP
Install
$ npx -y skills add artokun/comfyui-mcp --skill color-correction --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/color-correction

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The summary Claude sees to decide when to auto-load this skill.

Diagnose and fix video/image color OBJECTIVELY with the get_image (action:"analyze_color") tool (scopes/stats such as black/white points, contrast, saturation, clipping, cast) instead of eyeballing a contact sheet. Covers the "washed out" signature, why reference color-match

SKILL.md

color-correction.SKILL.md
name: color-correction
description: Diagnose and fix video/image color OBJECTIVELY with the get_image (action:"analyze_color") tool (scopes/stats such as black/white points, contrast, saturation, clipping, cast) instead of eyeballing a contact sheet. Covers the "washed out" signature, why reference color-match (mkl/ColorMatch/ColorMatchAdobe) CAN'T add contrast a flat source lacks, the levels/contrast-stretch fix (core AdjustContrast / CurveEditor), the measure→fix→re-measure loop, the side-by-side sandbox pattern, and where to place the fix in a render graph (after decode, before save). Use when a render looks washed out / flat / dull / over-saturated / color-cast, or when deciding between a color-match and a contrast/levels fix.
globs:
  - "**/*.json"
  - "**/packs/**"

Color Correction (measure, don't eyeball)

The core principle

You cannot reliably judge color from a storyboard or contact sheet. "Is it washed out?" flip-flops by eye, especially on AI-gen video. Make color measurable with the `get_image (action:"analyze_color")` MCP tool, read the numbers like a colorist reads scopes, pick the fix the data points to, then re-measure to confirm. The whole skill is this loop:

extract a frame ─► get_image (action:"analyze_color") ─► read black/white points + contrast + saturation
       ▲                                          │
       │                                          ▼
   re-measure  ◄──── apply fix (levels / contrast / match) ◄── diagnose from the numbers

> Origin: on a WAN-Animate render we argued for many turns over whether the clip was > "washed out." The instant we measured it, the answer was unambiguous and the *correct* > fix (a contrast stretch, not the color-match nodes we'd been adding) fell straight out.

---

The `get_image (action:"analyze_color")` tool

Read-only. Source = `asset_id`, a ComfyUI output ref (`filename`/`subfolder`/`type`), or an image `path` (absolute, or under the output dir). It returns per-image stats, heuristic flags, a one-line verdict, and optionally an overlaid R/G/B/luma histogram PNG.

get_image({ action: "analyze_color", filename: "render_00007_.png" })       # absolute numbers
get_image({ action: "analyze_color", path: "frame.png", reference_path: "src.jpg" })  # + shot-match deltas
get_image({ action: "analyze_color", filename: "x.png", histogram: true })  # + histogram image

For videos, `get_image (action:"analyze_color")` is image-only (no ffmpeg dep). Extract a frame first with the ComfyUI venv's cv2:

"<comfy-venv>/python" -c "import cv2; c=cv2.VideoCapture(r'IN.mp4'); n=int(c.get(7)); \
  c.set(1, n//2); _,f=c.read(); cv2.imwrite(r'frame.png', f)"

Grab the middle frame, or frame 0. For window-drift checks grab a frame from each window.

What the numbers mean (8-bit)

| Field | Reads like a scope | Healthy-ish | |---|---|---| | `luma.blackPoint` (1st pct) | where shadows bottom out | ~0–16 (lifted if >16) | | `luma.whitePoint` (99th pct) | where highlights top out | ~240–255 (dim if <235) | | `luma.contrast` (std) | overall punch | ~45+ (flat if <45) | | `luma.dynamicRange` | white−black | wide is good | | `saturation.meanSaturation` (HSV S) | vectorscope spread | ~0.25+ (dull if <0.22) | | `channels.{r,g,b}Mean` + `castHint` | RGB parade / white balance | spread <~12 = neutral | | `luma.clippedHighPct/LowPct` | blown / crushed pixels | keep low (<~2%) |

Flags: `washedOut, lowContrast, liftedBlacks, dimHighlights, lowSaturation, colorCast`.

---

The "washed out" signature

Washed out means compressed tonal range, and it has an exact fingerprint:

  • `whitePoint` well below 255 (e.g. 191), so highlights never reach white
  • `blackPoint` lifted off 0 (e.g. 45), giving milky shadows
  • `contrast` low (std < 45)
  • often *normal* saturation. Washout is usually not a saturation problem.

If you see that, the fix is a levels / contrast stretch, not a color match. In a real case, a WAN-Animate frame measured blackPoint 45 / whitePoint 191 / contrast 43, clearly a range problem; saturation 0.25 was fine.

---

The load-bearing insight: a reference-match can't add contrast the source lacks

The instinct is to "match the render to the input photo" with a color-match node (`ColorMatchV2` mkl/hm, `ImageColorMatchAdobe+`, easy `imageColorMatch`). Measure the reference first. If the reference is itself flat (e.g. a casual phone selfie with blackPoint 40, contrast 44), matching to it cannot produce punch; you'll match your way to the *same* flat numbers. In the real case, mkl and Adobe matches both left the frame flagged `washedOut` (whitePoint only crept from 191 to ~218).

So:

  • Use a reference-match (`ColorMatchV2`, `ImageColorMatchAdobe+`) when you want to *match

a known-good graded frame or shot-match across clips*, and the reference is actually good.

  • Use a levels / contrast stretch when the defect is compressed range (the washout case).

It targets full range *regardless* of the reference. This is usually the real fix.

---

The fix: contrast / levels stretch (core nodes, no install)

`AdjustContrast` (core `comfy_extras.nodes_dataset`, category *image/adjustments*) has one `factor` (1.0 = none, >1 = more). It pivots around mid-gray, so it pushes the white point up and the black point down together. Tune it by measurement, not feel. A real measured sweep on the washout frame:

| factor | blackPoint | whitePoint | contrast | sat | clippedHigh | verdict | |---|---|---|---|---|---|---| | 1.3 | 29 | 239 | 56 | 0.33 | **0%** | ✅ not washed (slightly soft) | | ~1.4 | ~20 | ~247 | ~60 | ~0.38 | ~1–2% | ✅ **sweet spot** | | 1.6 | 7 | 254 | 67 | 0.44 | **7.2%** ⚠️ | punchy but blows highlights |

Pick the factor that lands whitePoint ~248 to 255 with `clippedHighPct` < ~2%. Going too far (1.6 here) blows highlights *and* over-warms, because per-channel contrast drops blue more than red and `castHint` worsens. The sweet spot was ~1.4.

Other levers when contrast alone isn't enough: -

Read more
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