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 โ can you fix them all". Outputs direct final image URLs plus an in-chat preview grid and optional Firefly Board link. Access: ๐ Signed-In required | Gen AI: โ
What this skill does
# Adobe Batch Edit Photos
A batch editing pipeline focused on **visual cohesion** โ 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 | Tool | Notes |
| ------------------- | ------------------------------------------------- | ---------------------------------------------- |
| Ingest | `asset_add_file` | Interactive file picker |
| Straighten | `image_auto_straighten` | Per image |
| Auto-tone | `image_apply_auto_tone` | Per image, `type: "cameraRawFilter"` |
| Exposure | `image_adjust_exposure` | Batch โ fine-tune option (brighter/darker) |
| Highlights | `image_adjust_highlights` | Batch โ fine-tune option |
| Shadows | `image_adjust_dark_portions` | Batch โ fine-tune option |
| Bright areas | `image_adjust_light_portions` | Batch โ fine-tune option |
| Brightness/Contrast | `image_adjust_brightness_and_contrast` | Batch, if requested |
| Vibrance/Saturation | `image_adjust_vibrance_and_saturation` | Batch, if requested |
| Color temperature | `image_adjust_color_temperature` | Batch โ key for "warm", "cool", "golden" looks |
| Look preset | `image_apply_preset` | Per image, core style vehicle |
| Face detect | `image_select_subject` with `bodyParts: ["Face"]` | Per image, only if crop focus needed |
| Background blur | `image_apply_gaussian_blur` | Per image, only if explicitly requested |
| Crop | `image_crop_and_resize` | Per image, optional |
| Sample preview | `asset_preview_file` | Before/after on image[0] only |
| Final preview | `asset_preview_file` | Batch assets array |
| Firefly Board | `create_firefly_board` | All 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.
```json
{ "skill_name": "adobe-batch-edit-photos", "skill_version": "1.0.1" }
```
---
## Step 1 โ 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 โ 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 โ the preview and confirm gate always runs regardless of how clearly preferences were stated.
**B โ 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:
```
๐ท Got [N] photo(s)! Based on what you said, I'll go with:
- Look: Moody & Cinematic
- Tweaks: Recover blown highlights
Just one thing โ do you want a crop?
```
Then call `AskUserQuestion` with Question 3 only.
**C โ Nothing specified:** Post the full intro and show all 3 questions:
```
๐ท 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? ๐
```
The full `AskUserQuestion` questions (use only the ones that are still open):
```
Question 1 (single_select):
question: "๐จ Pick a base look"
options:
- "Auto (balanced, neutral)"
- "Warm & Golden โ cozy, travel, golden hour"
- "Bright & Airy โ clean, light, lifestyle"
- "Moody & Cinematic โ dramatic, contrasty, desaturated"
- "Cool & Fresh โ clear skies, travel, blue tones"
- "Vibrant & Punchy โ vivid, bold, social-ready"
- "Muted & Film โ faded, analog, editorial"
Question 2 (multi_select):
question: "๐๏ธ 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: "โ๏ธ Crop ratio? (optional)"
options:
- "No crop โ 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: "๐ฏ How should the crop be framed?"
options:
- "Center โ crop from center of image"
- "Smart crop โ 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 โ it almost always produces a better result than a pure center cut.
### Look โ Parameter Mapping
**Base look โ `image_adjust_color_temperature` + `image_apply_preset` + adjustments:**
| Look | Color Temp (a, b, luminance) | Preset | Saturation/Vibrance | Brightness/Contrast |
| ----------------- | ---------------------------- | ------------------------------ | ---------------------------- | ------------------- |
| Auto (balanced) | none | `Adaptive: Auto Tone` | none | none |
| Warm & Golden | a=32, b=120, luminance=67 | `Adaptive: Subject - Warm Pop` | vibrance +15 | none |
| Bright & Airy | a=20, b=60, luminance=62 | `Adaptive: Subject - Pop` | saturation -10, vibrance +10 | brightness +15 |
| Moody & Cinematic | a=20, b=-50, luminance=45 | `Adaptive: Sky - Dark Drama` | saturation -20 | contrast +25 |
| Cool & Fresh | a=18, b=-123, luminance=45 | `Adaptive: Sky - Blue Drama` | vibrance +10 | none |
| Vibrant & Punchy | none | `Adaptive: Subject - Pop` | vibrance +30, saturation +15 | contrast +10 |
| Muted & Film | none | none Related in Image & Video
watch
IncludedWatch a video (URL or local path). Downloads with yt-dlp, extracts auto-scaled frames with ffmpeg, pulls the transcript from captions (or Whisper API fallback), and hands the result to Claude so it can answer questions about what's in the video.
physical-ai-defect-image-generation
IncludedUse when the user wants to orchestrate defect image generation, run associated setup, or handle outputs on OSMO. The Day 0 path handles cold-start with USD-to-ROI, image-edit augmentation, and AnomalyGen to create initial PCBA datasets. The Day 1 path performs inference and labeling on real images. This skill helps with first-time asset setup, creation of finetuning checkpoints, and configuring deployment. Trigger keywords: defect image generation, dig workflow, dig pipeline, defect image detection workflow, aoi pipeline, aoi anomalygen, usd2roi anomalygen, day 0 pcba, day 1 pcba, day 1 real-photo alignment, day 1 manual roi, metal surface anomaly, glass defect, anomalygen finetune, setup_pcb, setup_metal, setup_glass, setup_pretrained, dig setup, dig datasets, dig pretrained checkpoint, dig image-edit endpoint.
accelint-react-best-practices
IncludedReact performance optimization and best practices. ALWAYS use this skill when working with any React code - writing components, hooks, JSX; refactoring; optimizing re-renders, memoization, state management; reviewing for performance; fixing hydration mismatches; debugging infinite re-renders, stale closures, input focus loss, animations restarting; preventing remounting; implementing transitions, lazy initialization, effect dependencies. Even simple React tasks benefit from these patterns. Covers React 19+ (useEffectEvent, Activity, ref props). Triggers - useEffect, useState, useMemo, useCallback, memo, inline components, nested components, components inside components, re-render, performance, hydration, SSR, Next.js, useDeferredValue, combined hooks.
elevenlabs-agents
IncludedBuild conversational AI voice agents with ElevenLabs Platform using React, JavaScript, React Native, or Swift SDKs. Configure agents, tools (client/server/MCP), RAG knowledge bases, multi-voice, and Scribe real-time STT. Use when: building voice chat interfaces, implementing AI phone agents with Twilio, configuring agent workflows or tools, adding RAG knowledge bases, testing with CLI "agents as code", or troubleshooting deprecated @11labs packages, Android audio cutoff, CSP violations, dynamic variables, or WebRTC config. Keywords: ElevenLabs Agents, ElevenLabs voice agents, AI voice agents, conversational AI, @elevenlabs/react, @elevenlabs/client, @elevenlabs/react-native, @elevenlabs/elevenlabs-js, @elevenlabs/agents-cli, elevenlabs SDK, voice AI, TTS, text-to-speech, ASR, speech recognition, turn-taking model, WebRTC voice, WebSocket voice, ElevenLabs conversation, agent system prompt, agent tools, agent knowledge base, RAG voice agents, multi-voice agents, pronunciation dictionary, voice speed control, elevenlabs scribe, @11labs deprecated, Android audio cutoff, CSP violation elevenlabs, dynamic variables elevenlabs, case-sensitive tool names, webhook authentication
humanizer
IncludedHumanize AI-generated text by detecting and removing patterns typical of LLM output. Rewrites text to sound natural, specific, and human. Uses 28 pattern detectors, 560+ AI vocabulary terms across 3 tiers, and statistical analysis (burstiness, type-token ratio, readability) for comprehensive detection. Use when asked to humanize text, de-AI writing, make content sound more natural/human, review writing for AI patterns, score text for AI detection, or improve AI-generated drafts. Covers content, language, style, communication, and filler categories.
generating-mermaid-diagrams
IncludedSalesforce architecture diagrams using Mermaid with ASCII fallback. Use this skill when generating text-based diagrams for Salesforce architecture, OAuth flows, ERDs, integration sequences, or Agentforce structure. TRIGGER when: user says "diagram", "visualize", "ERD", or asks for sequence diagrams, flowcharts, class diagrams, or architecture visualizations in Mermaid. DO NOT TRIGGER when: user wants PNG/SVG image output (use generating-visual-diagrams), or asks about non-Salesforce systems.