本文へ移動
cccskills
無料GitHub で公開

adobe-batch-edit-photos

Apply consistent photo adjustments across a set of images so they look like they were edited together. Use this skill whenever the user says "make my photos look cohesive", "give all these the same style", "apply a warm and golden feel to all of these", "make this cinematic", "match the look across my photos", "edit all my travel photos the same way", "batch edit these", "make these consistent", "fix my phone photos", or uploads a folder of photos and wants a unified, polished result. Also triggers for requests like "apply a preset to all of these", "make these look professional", or "they were shot in mixed lighting — can you fix them all". Outputs direct final image URLs plus an in-chat preview grid and optional Firefly Board link. Access: 🔐 Signed-In required | Gen AI: ❌

インストール方法を見る

含まれるファイル(1)

  • SKILL.md24.4 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Adobe Batch Edit Photos

A batch editing pipeline focused on visual cohesion — making a set of photos look like they were edited together. The user picks a look (or describes one), and Claude applies it consistently across every image using Adobe creativity tools.

The core insight: users who want "cohesion" care less about per-image perfection and more about the whole set reading as intentional. Prioritize consistency of tone and color over squeezing the best out of any single image.


Tool Reference

StepToolNotes
Ingestasset_add_fileInteractive file picker
Straightenimage_auto_straightenPer image
Auto-toneimage_apply_auto_tonePer image, type: "cameraRawFilter"
Exposureimage_adjust_exposureBatch — fine-tune option (brighter/darker)
Highlightsimage_adjust_highlightsBatch — fine-tune option
Shadowsimage_adjust_dark_portionsBatch — fine-tune option
Bright areasimage_adjust_light_portionsBatch — fine-tune option
Brightness/Contrastimage_adjust_brightness_and_contrastBatch, if requested
Vibrance/Saturationimage_adjust_vibrance_and_saturationBatch, if requested
Color temperatureimage_adjust_color_temperatureBatch — key for "warm", "cool", "golden" looks
Look presetimage_apply_presetPer image, core style vehicle
Face detectimage_select_subject with bodyParts: ["Face"]Per image, only if crop focus needed
Background blurimage_apply_gaussian_blurPer image, only if explicitly requested
Cropimage_crop_and_resizePer image, optional
Sample previewasset_preview_fileBefore/after on image[0] only
Final previewasset_preview_fileBatch assets array
Firefly Boardcreate_firefly_boardAll edited outputs

Step 0 - prereq: Initialize Adobe Tools

Call adobe_mandatory_init first. This returns file handling rules and tool routing guidance required for the rest of the workflow.

{ "skill_name": "adobe-batch-edit-photos", "skill_version": "1.0.1" }

Step 1 — Entitlement Check

Now that adobe_mandatory_init confirmed that the "Adobe for creativity" connector is live, check which tools are available through the "Adobe for creativity" connector by cross checking against the Tool Reference table above.


Step 2: Image Ingestion

Call asset_add_file with no parameters to open the file picker:

Tool: asset_add_file
Params: {}

Step 3: Understand the Desired Look

Once URIs are obtained, scan the conversation to infer as many preferences as possible before asking anything:

  • Look: inferrable from words like "warm", "golden", "cinematic", "moody", "bright and airy", "muted", "film", "cool", "vibrant", "punchy"
  • Fine-tune tweaks: inferrable from "recover highlights", "lift shadows", "more contrast", "blown out", "too dark", "more vibrant", "desaturate"
  • Crop: inferrable from "no crop", "square", "1:1", "portrait crop", "keep framing", etc.

Three cases:

A — Everything clear from context: Skip AskUserQuestion entirely. Post the confirmation message, then proceed directly to Step 3b (sample preview). Do NOT start the full batch — the preview and confirm gate always runs regardless of how clearly preferences were stated.

B — Some things clear, some not: Confirm what you've inferred upfront, then call AskUserQuestion with only the questions that remain unanswered. For example, if the look and a tweak are clear but crop isn't, post:

📷 Got [N] photo(s)! Based on what you said, I'll go with:
- Look: Moody & Cinematic
- Tweaks: Recover blown highlights

Just one thing — do you want a crop?

Then call AskUserQuestion with Question 3 only.

C — Nothing specified: Post the full intro and show all 3 questions:

📷 Got [N] photo(s)! I'll apply consistent edits across all of them so
the set looks cohesive.

What kind of look are you going for? 👇

The full AskUserQuestion questions (use only the ones that are still open):

Question 1 (single_select):
  question: "🎨 Pick a base look"
  options:
    - "Auto (balanced, neutral)"
    - "Warm & Golden — cozy, travel, golden hour"
    - "Bright & Airy — clean, light, lifestyle"
    - "Moody & Cinematic — dramatic, contrasty, desaturated"
    - "Cool & Fresh — clear skies, travel, blue tones"
    - "Vibrant & Punchy — vivid, bold, social-ready"
    - "Muted & Film — faded, analog, editorial"

Question 2 (multi_select):
  question: "🎛️ Fine-tune (optional)"
  options:
    - "Recover blown highlights"
    - "Lift dark shadows"
    - "Boost contrast"
    - "Boost color intensity"
    - "Desaturate / muted tones"
    - "Adjust exposure (brighter/darker)"
    - "Tune bright areas"
    - "Blur background (heavy)"
    - "None"

Question 3 (single_select):
  question: "✂️ Crop ratio? (optional)"
  options:
    - "No crop — keep original framing"
    - "1:1 square"
    - "4:5 portrait"
    - "16:9 wide"
    - "4:3 standard"

Question 4 (single_select):  [only ask if Q3 is not "No crop"]
  question: "🎯 How should the crop be framed?"
  options:
    - "Center — crop from center of image"
    - "Smart crop — detect subject/face and frame around it"

Wait for the user's reply before proceeding.

Note on Question 4: If the user's message already implies a framing preference (e.g. "center crop", "crop to my face", "frame around the subject"), skip Q4 and infer directly. If the user specifies a ratio but not a framing method, default to Smart crop — it almost always produces a better result than a pure center cut.

Look → Parameter Mapping

Base look → image_adjust_color_temperature + image_apply_preset + adjustments:

LookColor Temp (a, b, luminance)PresetSaturation/VibranceBrightness/Contrast
Auto (balanced)noneAdaptive: Auto Tonenonenone
Warm & Goldena=32, b=120, luminance=67Adaptive: Subject - Warm Popvibrance +15none
Bright & Airya=20, b=60, luminance=62Adaptive: Subject - Popsaturation -10, vibrance +10brightness +15
Moody & Cinematica=20, b=-50, luminance=45Adaptive: Sky - Dark Dramasaturation -20contrast +25
Cool & Fresha=18, b=-123, luminance=45Adaptive: Sky - Blue Dramavibrance +10none
Vibrant & PunchynoneAdaptive: Subject - Popvibrance +30, saturation +15contrast +10
Muted & Filmnonenonesaturation -35, vibrance -10contrast +10

Fine-tune → tool parameters:

  • "Recover blown highlights" → image_adjust_highlights → amount: -60
  • "Lift dark shadows" → image_adjust_dark_portions → amount: +40
  • "Boost contrast" → image_adjust_brightness_and_contrast → contrast: 30
  • "Boost color intensity" → image_adjust_vibrance_and_saturation → vibrance: 30
  • "Desaturate / muted tones" → image_adjust_vibrance_and_saturation → saturation: -30
  • "Adjust exposure (brighter/darker)" → image_adjust_exposure → exposure: +0.5 (brighter) or exposure: -0.5 (darker); infer direction from context, default to +0.3 if unspecified
  • "Tune bright areas" → image_adjust_light_portions → amount: +20
  • "Blur background (heavy)" → image_apply_gaussian_blur → blurRadius: 12, blurTarget: "background"
  • "None" → skip fine-tune step entirely

Crop:

  • "No crop" → skip Step 7 entirely
  • Ratio + "Center" → image_crop_and_resize with fit: "reframe", that ratio as output, align: { x: 0.5, y: 0.5 } (pure center cut)
  • Ratio + "Smart crop" → image_crop_and_resize with fit: "reframe", that ratio as output, focus: "face" if portraits/people likely, else focus: "subject" (smart reframe around detected subject at the chosen ratio)

After receiving selections, confirm the settings back to the user:

✅ Got it — running with:
- Look: [selected look]
- Tweaks: [list if any, or "none"]
- Crop: [ratio or "no crop"] + [Center / Smart crop]
- Background blur: [yes/no]

Then proceed immediately to Step 3b (sample preview) — do not start the full batch yet.


Step 3a: Large Batch Warning (N > 5)

Include this as part of the Step 3b confirmation prompt (after the before/after preview) when N > 5:

⏱ Estimated time for [N] images:
  6–10 → ~3–5 min
  11–20 → ~5–10 min
  20+ → 10+ min

Feel free to step away — I'll post a ✅ summary with download links when done.

Step 3b: Sample Preview (Before/After on Image 1)

Before running the full batch, process the first image only through the complete pipeline (Steps 4–8) using the confirmed settings. This gives the user a real preview of exactly what will be applied to every image.

  1. Run the full pipeline on sourceURIs[0] only (straighten → tone → look → fine-tune → blur → crop).
  2. Call asset_preview_file directly with both the original source URL and the processed output URL — do NOT resize either through image_crop_and_resize first, as that introduces white bars or unwanted cropping:
asset_preview_file({
  assets: [
    { name: "Before", presignedAssetUrl: sourceURIs[0] },
    { name: "After",  presignedAssetUrl: processed_url }
  ]
})
  1. Post this message (append the large-batch timing note here if N > 5):
👆 Here's a before/after preview using your first photo and the settings you selected.

How does it look?
  1. Call AskUserQuestion with a single question:
Question (single_select):
  question: "Ready to run the full batch?"
  options:
    - "✅ Looks great — run all [N] images"
    - "🎛️ Adjust settings"
    - "❌ Cancel"

If "Looks great": Start the full batch on the remaining images (sourceURIs[1…]). Reuse the already-processed image[0] result — do not reprocess it.

If "Adjust settings": Re-show the full AskUserQuestion set from Step 3. Once new settings are confirmed, ask whether the user wants another preview or wants to go straight to the full batch:

Question (single_select):
  question: "Want to preview the new settings first, or run all images now?"
  options:
    - "👁 Preview first"
    - "🚀 Run all [N] images now"
  • If "Preview first": repeat Step 3b with the new settings (process image[0] again, show before/after, offer the same Looks great / Adjust / Cancel gate).
  • If "Run all now": start the full batch immediately on all sourceURIs with the new settings. Do not reuse the earlier image[0] result — reprocess it with the updated settings. If "Cancel": Acknowledge and stop. Do not process any images.

Step 4: Auto-Straighten (per image)

Tool: image_auto_straighten
Params:
  imageURIs: ["<source_uri_N>"]
  options:
    uprightMode: "auto"
    constrainCrop: true

Output: results[0].outputUrl → straightened_urls[]

On failure: use original URI, note "straighten skipped" for that image.


Step 5: Auto-Tone (per image)

Tool: image_apply_auto_tone
Params:
  imageURI: "<straightened_url_N>"
  options:
    type: "cameraRawFilter"
  outputFileType: "jpeg"

Use type: "cameraRawFilter" for image_apply_auto_tone. Output: results[0].outputUrl → toned_urls[]


Step 6: Apply the Look (per image)

Apply the look in this order per image, chaining outputs:

6a: Color Temperature (if the look requires it — see mapping table)

image_adjust_color_temperature supports a batch imageURIs array. Pass all toned URLs at once for efficiency:

Tool: image_adjust_color_temperature
Params:
  imageURIs: ["<toned_url_1>", "<toned_url_2>", ...]
  options:
    a: <value from mapping>         # green-red axis (-128–127)
    b: <value from mapping>         # blue-yellow axis (-128–127)
    luminance: <value from mapping> # 0–100

Output: results[N].outputUrl → color_temp_urls[]

6b: Look Preset (if the look uses one — see mapping table)

Tool: image_apply_preset
Params:
  imageURI: "<color_temp_url_N>"
  options:
    presetName: "<preset from mapping>"

6c: Vibrance / Saturation (if the look requires it)

Tool: image_adjust_vibrance_and_saturation
Params:
  imageURIs: ["<previous_url_N>"]
  options:
    vibrance: <value>
    saturation: <value>

6d: Brightness + Contrast (if the look requires either — combine into one call)

Tool: image_adjust_brightness_and_contrast
Params:
  imageURIs: ["<previous_url_N>"]
  options:
    brightness: <value>   # omit if not needed for this look
    contrast: <value>     # omit if not needed for this look

Combining brightness and contrast into a single call saves a round trip and produces the same result as two sequential calls.

The goal is consistency: apply the same parameter values to every image, even if some images might technically look better with different values. Cohesion beats perfection here.

On 403 (entitlement) for image_apply_preset: Skip the preset for all images. Note in the delivery summary: "[Preset name] was skipped — not included in your Adobe plan." Continue with the rest of the look adjustments.


Step 7: Fine-Tune Adjustments (batch, if selected)

Apply user-selected tweaks across all images at once. All of these tools accept a batch imageURIs array — chain from the look output:

Tool: image_adjust_highlights / image_adjust_dark_portions / image_adjust_brightness_and_contrast /
      image_adjust_vibrance_and_saturation / image_adjust_exposure / image_adjust_light_portions
Params:
  imageURIs: ["<look_url_1>", "<look_url_2>", ...]
  options:
    <values from mapping>

Run each selected tweak in sequence, chaining outputs. If "Boost contrast" is selected AND the look already calls image_adjust_brightness_and_contrast for brightness (e.g. Bright & Airy), merge them into a single call with both brightness and contrast values rather than running two separate calls.

Background blur (if selected, per image):

Tool: image_apply_gaussian_blur
Params:
  imageURIs: ["<url_N>"]
  options:
    blurRadius: 12
    blurTarget: "background"

Step 8: Crop (per image, if requested)

If "No crop" was selected, skip this step entirely.

Both crop modes use the same fit: "reframe" at the chosen ratio — the difference is in how the frame is positioned within the image.

Center crop — cuts to the target ratio from the geometric center:

Tool: image_crop_and_resize
Params:
  imageURI: "<adjusted_url_N>"
  options:
    output: "<ratio>"        # "1:1", "4:5", "16:9", "4:3"
    fit: "reframe"
    align: { x: 0.5, y: 0.5 } # geometric center
  outputFileType: "jpeg"

Smart crop — same ratio, but positions the frame around the detected subject or face rather than the geometric center. The subject stays in frame even if they're off-center in the original:

Tool: image_crop_and_resize
Params:
  imageURI: "<adjusted_url_N>"
  options:
    output: "<ratio>"   # "1:1", "4:5", "16:9", "4:3"
    fit: "reframe"
    focus: "face"       # or "subject" for non-portrait scenes
  outputFileType: "jpeg"

Collect as final_urls[]. If no crop: final_urls[] = outputs from Step 7 (or Step 6 when no fine-tunes are selected).


Step 9: Preview

Pass the final output URLs directly to asset_preview_file — do NOT run them through image_crop_and_resize first. Adding a resize step introduces white bars (from fit: "pad") or crops subjects (from fit: "reframe"). asset_preview_file handles its own thumbnailing correctly.

asset_preview_file({
  assets: [
    { name: "photo_1.jpg", presignedAssetUrl: final_url_1 },
    // ... one per image
  ]
})

If asset_preview_file fails, present the final output URLs as plain text links in the completion summary.

Before/after preview (Step 3b): Same rule applies — pass the original source URL and the processed URL directly to asset_preview_file. Do not resize either.

Create Firefly Board

Call the firefly board tool with the final output urls as follows:

create_firefly_board({
  import_adobe_storage: [
    final_output_url_1,
    final_output_url_2,
    // ...
  ]
})

Board link handling:

  • create_firefly_board returns a board URL. Extract it and store as board_url.
  • If board_url is present and non-empty, include it in the completion message.
  • If the call throws an error or returns no URL: omit the board link and note "Firefly Board unavailable" in the summary (retrying does not help). Then post the completion message. The preview grid is included in every completion message. The board link is included whenever board_url was returned.

If N ≤ 3:

✅ Done! [N] photos edited with a consistent [look name] look.

📥 Download:
• Photo 1 → <final_url_1>
• ...

🎨 View in Firefly Board → <board_url>   ← always include if board_url is set

Look applied: [look name] → [brief description of what was applied]

If N > 3:

✅ Done! [N] photos edited with a consistent [look name] look.

📥 Your edited photos:
• Photo 1 → <final_url_1>
• Photo 2 → <final_url_2>
• ...

🎨 View in Firefly Board → <board_url>   ← always include if board_url is set

Look applied: [look name] → [brief description of what was applied]

Verbosity Rule

Report only: major stage starts, per-image failures (logged once), and the final summary.

  • When a major stage starts (e.g. "Applying Warm & Golden look to [N] images…")
  • Any per-image failure (log once, continue)
  • Final summary with grid + download links

Output Extraction

All pipeline tools return:

{ "results": [{ "success": true, "outputUrl": "https://..." }] }

Read results[N].outputUrl. On success: false → see Error Handling.


Error Handling

SituationAction
image_apply_preset returns 403Skip preset for all images (Pattern 1). Note in summary. Continue with other look steps.
Any tone/color tool returns 403Skip that step. Note in summary. Continue.
Any tool returns "No approval received"Treat the same as a 403 entitlement error. For optional steps (presets, fine-tune adjustments, preview), skip and note in summary. Retrying does not help for this error — continue per the rules above.
Any tool returns 401Ask user to re-authenticate via Adobe OAuth and retry.
Any tool returns "file too large or corrupted"Stop processing that image immediately. Do not retry, do not attempt alternative URLs. Tell the user: "I couldn't process [filename] — it's either too large or the file may be damaged. Try re-uploading a smaller version, or check that the file opens correctly on your end." Flag the image in the summary and continue with remaining images.
asset_add_file shows no filesRemind user to select files in the picker.
image_auto_straighten failsUse original URI; note "straighten skipped".
image_apply_auto_tone failsUse straightened URI; note in summary.
Any adjustment tool failsUse previous step's output; note in summary.
image_apply_gaussian_blur failsUse previous output; note "blur skipped".
image_crop_and_resize failsUse blur/adjusted output as final; note in summary.
asset_preview_file returns "No approval received"Present final output URLs as plain text links in the summary instead.
All steps fail on one imageReturn original URI; flag clearly in summary.

Hard Constraints

  • Every image in the batch is processed; failures are flagged rather than silently skipped.
  • image_apply_auto_tone is called with type: "cameraRawFilter".
  • Apply the same parameter values to every image in the batch (cohesion over perfection).
  • Adaptive presets are off by default — only run them as part of a look.
  • Background blur uses image_apply_gaussian_blur with blurTarget: "background" (image_apply_lens_blur is not used here).
  • Completion is posted as a clear in-chat message (no push notifications).

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Analyzes a multi-step conversion funnel to find where visitors drop off and which steps have the worst leakage. Use this skill when someone describes a journey and asks about conversion rates, drop-off, fallout, or step completion. Trigger for "analyze our checkout funnel," "where are visitors dropping off," "what's our add-to-cart to purchase conversion rate," "funnel analysis," "show me fallout between steps," or "which step loses the most visitors."

日本語の概要は準備中です。原文の説明を表示しています。

OCIOStateOfNebraska/stateofnebraska-aem32026年10月9日 更新

Generates a concise, executive-ready performance summary covering key metrics, trends, and what's driving movement. Use this skill when someone needs to produce a briefing, executive summary, performance narrative, or stakeholder readout — for example, "write an exec summary of last week's performance," "create a performance briefing for our leadership team," "produce a monthly business review summary," "what should I tell executives about our metrics," or "generate a performance narrative." Also trigger for "QBR summary," "weekly business review," or "stakeholder briefing."

日本語の概要は準備中です。原文の説明を表示しています。

OCIOStateOfNebraska/stateofnebraska-aem32026年10月9日 更新

Produces a compact KPI digest showing how key metrics changed over a period and what's driving the movement. Use this skill when someone asks for a performance summary, a weekly recap, a morning briefing, a KPI update, or any variation of "how did we do this week/month." Also trigger for "give me a performance overview," "what moved in the last 7 days," "pull our AA KPI report," or "summarize our metrics."

日本語の概要は準備中です。原文の説明を表示しています。

OCIOStateOfNebraska/stateofnebraska-aem32026年10月9日 更新

Compares the performance of two or more audience segments across key metrics side by side. Use this skill when someone wants to compare audiences or visitor groups — for example, "how do mobile visitors compare to desktop on conversion," "compare new vs. returning visitors," "show me the difference between these two segments," "compare these audiences on our KPIs," or "which segment performs better." Also trigger for "segment comparison" or "audience comparison."

日本語の概要は準備中です。原文の説明を表示しています。

OCIOStateOfNebraska/stateofnebraska-aem32026年10月9日 更新

Identifies which items (pages, campaigns, products, channels, regions) had the biggest increases or decreases for a key metric between two time periods. Use this skill when someone asks "what's up and what's down," "which campaigns moved the most," "top gainers and losers," "what pages are trending," "show me what changed by channel," or any variation of identifying the biggest movers and decliners for a metric.

日本語の概要は準備中です。原文の説明を表示しています。

OCIOStateOfNebraska/stateofnebraska-aem32026年10月9日 更新

Scan an AEM Edge Delivery Services page for WCAG 2.1 AA accessibility violations and generate specific fixes. Identifies missing alt text, heading hierarchy issues, link text problems, color contrast concerns, and EDS-specific accessibility patterns. Use when fixing accessibility issues, preparing for compliance audits, or remediating WCAG violations.

日本語の概要は準備中です。原文の説明を表示しています。

OCIOStateOfNebraska/stateofnebraska-aem32026年10月9日 更新

OCIOStateOfNebraska のスキルをすべて見る

このスキルの問題を報告する