Adobe Create Social Variations

Produces platform-ready images and videos from a single source file. Uses AI canvas expansion and subject-aware cropping to keep the subject in focus across all aspect ratios. Shows a lightweight 3-crop preview before a full-set run so framing issues are caught early — those crops are then reused in the final output.

Supported Input Types

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.

json
1{ "skill_name": "adobe-create-social-variations", "skill_version": "1.0.0" }

IMAGE WORKFLOW

Step 0 — Get the Source File

How you get the file depends on where it is:

After the file is available, detect image vs. video from mediaType. For images, proceed to Step 1.

Step 1 — Ask: Which Platforms?

Ask in a single question using AskUserQuestion with multi-select:

Full set / Instagram / TikTok / LinkedIn / Facebook / YouTube / Snapchat / X/Twitter / Pinterest / Threads

Set the test flag based on the user's answer:

• If "Full set" is selected → runTestPreview = true. Use all platforms. A 3-crop test preview will be shown before the full set is generated (see Step 4).
• If any specific platform(s) are selected → runTestPreview = false. Use only the selected platforms. Skip the test preview and go directly from Step 3 to Step 5.

The test preview is a useful safety net for large cross-platform batches, but unnecessary friction for a targeted 1–2 platform run.

Step 2 — Inspect Image & Set Focus Strategy

Inspect the image first using asset_inline_preview on the source file. Visual inspection produces far better focus decisions than guessing from the filename — and usually means you won't need to ask the user anything at all.

After inspecting, tell the user what you see and what focus strategy you're using, and invite a correction:

"I can see this is a [e.g. 'product shot of a tote bag on a neutral background']. I'll use [focus strategy] to keep [subject] centred across all crops. Does that sound right, or would you like me to focus on something else?"

Only ask a follow-up question if the image is genuinely ambiguous (multiple equally prominent subjects, or a scene with no clear focal point).

For images containing people, use "face" — prompt-based focus drifts to bodies rather than faces. Reserve { prompt: "..." } for non-human subjects.

⚠️ If the source image is significantly wider than it is tall (landscape), use 2000px top & bottom for the tall expand (not the default 960px) — this gives the portrait crop enough canvas to reframe around the subject. ⚠️ For the same landscape sources, also use 1500px left & right for the wide expand (not the default 960px) — 960px doesn't give the reframe enough room to pull the subject into centre for the ~2:1 landscape crop.

If the user corrects your assessment, update the focus strategy and confirm before proceeding.

Step 3 — Generative Expand (directly from source — no padding)

Expand the original image directly. Do not pad to square first — the AI produces better results extending real scene content than bridging across blank bars.

Run both expands before any crops:

// GROUP A — tall canvas (for 9:16 and 4:5 targets)
image_generative_expand(sourceURI, { top: 960, bottom: 960 }) → tallURI
// use 2000 top & bottom if source is significantly landscape

// GROUP B — wide canvas (for ~2:1 and 16:9 targets)
image_generative_expand(sourceURI, { left: 960, right: 960 }) → wideURI
// use 1500 left & right if source is significantly landscape

Square targets (1:1) crop directly from the source — no expand needed.

Expands originate from the original sourceURI — chained expands degrade output. ⚠️ If image_generative_expand returns 403 (entitlement), fall back to image_crop_and_resize with fit: "reframe" from sourceURI for all variants in that group. Note the fallback in the delivery summary.

Step 4 — Test Preview (Full set only — skip if runTestPreview = false)

If runTestPreview = false (specific platforms selected): skip this step and go directly to Step 5.

If runTestPreview = true (Full set): produce 3 representative test crops — one per aspect ratio family — before generating the full set.

Show all 3 via asset_preview_file and ask:

"Here are 3 test crops covering the main aspect ratios. Do the framing and expansion look good? I'll generate the full set once you approve."

These crops are reused in the final output — only the 9:16 story/reel crop needs to be generated after approval.

Step 5 — Generate All Platform Variants

If runTestPreview = true: proceed only after user approves test crops in Step 4. If runTestPreview = false: proceed immediately after Step 3.

Generate every variant in the Platform Specs table for each selected platform. Reuse test crop URIs only when dimensions are an exact match — for any different dimensions, run a fresh image_crop_and_resize.

Per-platform variants to generate:

Step 6 — Preview Full Set

Call asset_preview_file with all successfully generated URLs — including partial sets when some variants failed.

Step 7 — Delivery Summary

Present a clean summary table. Note any fallbacks or skipped steps clearly.

✅ Social media set complete!

| Platform  | Format         | Dimensions | Status        |
| --------- | -------------- | ---------- | ------------- |
| Instagram | Feed Square    | 1080×1080  | ✅ (from test) |
| Instagram | Feed Portrait  | 1080×1350  | ✅ (from test) |
| Instagram | Story / Reel   | 1080×1920  | ✅             |
| TikTok    | Video / Post   | 1080×1920  | ✅             |
| LinkedIn  | Post Landscape | 1200×627   | ✅ (from test) |
| LinkedIn  | Post Square    | 1080×1080  | ✅ (from test) |

If generative expand fell back to reframe:

⚠️ AI canvas expansion is not included in your current Adobe plan — smart reframe was used instead.

Platform Specs (Image)

⚠️ Snapchat's 250 KB limit requires quality: 2 — warn the user upfront when Snapchat is selected.

File naming convention: [basename]_[platform]_[descriptor]_[ratio].jpg Example: hero_instagram_story_9x16.jpg

VIDEO WORKFLOW

Step 0 — Get the Source File

Video tools require an assetId — not a URL. How you get it depends on where the file is:

If egress is disabled and the user has already dropped a video into chat, explain why it can't be used directly: "To resize your video I'll need you to select it via the file picker — this gives Adobe the asset ID it needs. I'll open it now."

Step 1 — Determine Video Type

If the user has already described or implied the video orientation (e.g. "I shot this on my phone in portrait" → clearly 9:16), skip this question and proceed. Otherwise ask:

"To suggest the best output sizes, it helps to know what kind of video this is. What type is it?"

Use AskUserQuestion with single-select:

Step 2 — Suggest Safe Output Sizes

Only suggest same-ratio resizes. Cross-ratio resizes (e.g. 16:9 → 9:16) produce black bars and are algorithmically penalised on TikTok and Instagram Reels. If a user asks for a cross-ratio resize, explain the limitation and offer same-ratio alternatives instead.

Present these as options with AskUserQuestion (multi-select).

Step 3 — Resize

⚠️ resizeVideoPoll is a deferred tool — load it first before attempting to poll. Direct calls without loading will fail with "not loaded" error.

For each selected size, call video_resize with the asset ID:

javascript
1video_resize({ assetId: sourceAssetId, width: W, height: H }) → { statusId }

Poll with resizeVideoPoll until complete. Poll 3–4 times with brief pauses before reporting slow progress to the user.

Step 4 — Preview

Call asset_preview_file with all completed outputs.

Step 5 — Delivery Summary

✅ Video resize complete!

| Size      | Ratio | Status |
| --------- | ----- | ------ |
| 1080×1920 | 9:16  | ✅      |
| 720×1280  | 9:16  | ✅      |

Note: Video resizing does not apply intelligent reframing — cross-ratio reformatting is out of scope for this skill.

Error Handling