adobe-batch-edit-photos（adobe 批量编辑照片）

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

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:

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

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).