AI Image Generation and Editing
zhayujie/CowAgent
Generates or edits images from text prompts through a Python script that picks an image backend based on which API keys are configured.
The AI image-editing router — inpainting/object removal, background removal, upscaling, outpainting, old-photo restoration, and retouch, routed task-first to the right engine.
Install AI Image Editing
$ npx skills add social-media-skills/skills --skill ai-image-editing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install social-media-skills/skills ai-image-editing --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-image-editing .claude/skills/ai-image-editing && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "ai-image-editing" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/ai-image-editing into .claude/skills/ai-image-editing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-image-editing", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/social-media-skills/skills/tree/main/skills/ai-image-editingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add social-media-skills/skills --skill ai-image-editing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install social-media-skills/skills ai-image-editing --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai-image-editing .agents/skills/ai-image-editing && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-image-editing" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/ai-image-editing into .agents/skills/ai-image-editing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-image-editing", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add social-media-skills/skills --skill ai-image-editing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install social-media-skills/skills ai-image-editing --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai-image-editing .cursor/skills/ai-image-editing && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ai-image-editing" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/ai-image-editing into .cursor/skills/ai-image-editing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-image-editing", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/social-media-skills/skills.git --path skills/ai-image-editing--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add social-media-skills/skills --skill ai-image-editing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install social-media-skills/skills ai-image-editing --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai-image-editing .gemini/skills/ai-image-editing && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ai-image-editing" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/ai-image-editing into .gemini/skills/ai-image-editing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-image-editing", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install social-media-skills/skills ai-image-editingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add social-media-skills/skills --skill ai-image-editing -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai-image-editing .github/skills/ai-image-editing && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ai-image-editing" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/ai-image-editing into .github/skills/ai-image-editing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-image-editing", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add social-media-skills/skills --skill ai-image-editing -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install social-media-skills/skills ai-image-editing --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/social-media-skills/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai-image-editing .opencode/skills/ai-image-editing && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ai-image-editing" agent skill from https://github.com/social-media-skills/skills/tree/main/skills/ai-image-editing into .opencode/skills/ai-image-editing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-image-editing", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
ai-image-editing- GitHub stars
- 134
- Token cost
- ~2.1k tokens
- SKILL.md length
- 888 words
- Files
- 6 (incl. references)
- Skills in repo
- 106
- Repo updated
- First seen
- Licence
- MIT
At a glance
The AI image-editing router — inpainting/object removal, background removal, upscaling, outpainting, old-photo restoration, and retouch, routed task-first to the right engine.
- Works in 2 steps: brand-profile + design-and-templates —… → before-after-and-transformation — the…
- Someone wants to remove an object/person from a photo
- SKILL.md covers The POV: fix the 5%, keep the…, Read these first, The framework: TOUCH and The reality (verify-quarterly), plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
AI Image Editing is an agent skill from social-media-skills/skills. The AI image-editing router — inpainting/object removal, background removal, upscaling, outpainting, old-photo restoration, and retouch, routed task-first to the right engine. Use when someone wants to remove an object/person from a photo, cut out backgrounds, upscale an image, extend an image to new aspect ratios, restore an old photo, fix a generated image, or asks which editing tool to use. Uses the TOUCH framework. Reads brand-profile + design-and-templates first. The agent names the task, routes to the right…
Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `evals/evals.json`, `references/ai-image-editing-2026-reality.md` and `references/scope-and-connections.md`).
It sits in Media & Creative, covering Image generation and Image editing. It works with Canva and Google Gemini. The repository describes itself as: 106 social media skills for AI agents - strategy, writing, video, design, platform growth, publishing, and analytics. Works with Claude, Cursor, OpenClaw, Hermes & 40+ agents. The licence is MIT.
When your agent uses it
- Someone wants to remove an object/person from a photo
- Cut out backgrounds
- Upscale an image
- Extend an image to new aspect ratios
Example prompts
- “/ai-image-editing”
Workflow steps
2 steps, taken from the first numbered list in SKILL.md.
- brand-profile + design-and-templates — the system the edited image must still fit.
- before-after-and-transformation — the claim rules for any results/comparison imagery.
What it can do on your machine
Read from SKILL.md and the folder at commit 6e30eeb. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
AI Image Editing loads about 2.1k tokens when it runs, and up to ~5.5k if it reads all its reference files. Until then it costs about 254 tokens; SKILL.md has 888 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from social-media-skills/skills at commit 6e30eeb, republished under its MIT licence (© social-media-skills). 888 words, ~2,095 tokens.
Download SKILL.mdSave it as
.claude/skills/ai-image-editing/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.- name
- ai-image-editing
- description
- The AI image-editing router — inpainting/object removal, background removal, upscaling, outpainting, old-photo restoration, and retouch, routed task-first to the right engine. Use when someone wants to remove an object/person from a photo, cut out backgrounds, upscale an image, extend an image to new aspect ratios, restore an old photo, fix a generated image, or asks which editing tool to use. Uses the TOUCH framework. Reads brand-profile + design-and-templates first. The agent names the task, routes to the right engine, writes the spec, and can call APIs where connected; the HUMAN judges every result at 100%; WoopSocial publishes. Honesty spine: an edited real photo is an edited claim — creative upscalers hallucinate detail (never on products/documents), no defect concealment, body-retouch disclosure honored, no watermark/provenance stripping. Distinct from image-prompt/flux/nano-banana (generation), canva (the design workflow), and before-after-and-transformation (the claim rules).
- version
- 1.0.0
ai-image-editing
The edit router — name the task, route the engine, one change at a time, uphold the real, check the seams,
hand off with rights. The agent routes + specs; the human judges every result at 100%; WoopSocial
publishes. (Ships with tools/integrations/ai-image-editing.md.)
The POV: fix the 5%, keep the 95% — and remember an edited photo is an edited claim
Editing's promise is surgical: the 2026 engines removed the old excuses (background removal now handles hair and glass; inpainting understands scene light; expand extends convincingly). The top-1% operator holds three lines the tool marketing won't. (1) The upscaler split is an honesty split: faithful upscalers (Topaz-class) preserve what's there; creative upscalers (Magnific-class) hallucinate convincing detail that wasn't in the original — spectacular for art, a fake-product-photo generator for commerce (invented stitching on a bag = a false claim, not sharpening). In-image text gets mangled — re-typeset it; no upscaler beats a reshoot. (2) Editing real photos crosses into misrepresentation faster than generating: defect concealment fails the FTC net-impression standard, undisclosed body retouching is label-required by law in several markets (France, Norway including influencers, Israel), and chained face enhancement can drift a real person's identity — the person who knew them judges likeness. (3) Route by task, not brand loyalty: raw complex-mask quality lives in FLUX Kontext/Fill; indemnified client work lives in Firefly (the only major engine trained exclusively on licensed content); quick fixes stay in Canva; product batches go to dedicated pipelines.
Read these first
- brand-profile + design-and-templates — the system the edited image must still fit.
- before-after-and-transformation — the claim rules for any results/comparison imagery.
The framework: TOUCH
(Depth: references/the-touch-framework.md.)
- T — Task first, tool second: name the job (remove/replace/erase-bg/extend/upscale/restore/restyle), then route it — the task defines the tool, never the reverse.
- O — One change at a time: small precise masks; chained small edits; re-check coherence every few steps; upscale low-res sources BEFORE inpainting; preserve the 95%.
- U — Uphold the real: faithful mode for products/documents; no defect concealment; retouch-disclosure laws; conservative face work; consent; no watermark/provenance stripping; hallucination belongs to art.
- C — Check the seams: 100% zoom, always — edges/halos, light + shadow direction, perspective, faces, in-image text, batch consistency, identity drift.
- H — Hand off with rights: source license + engine terms (Firefly indemnification vs FLUX outputs-vs-service) + disclosure labels; master as PNG/TIFF → WoopSocial.
The reality (verify-quarterly)
2026 editing: background removal handles hair/glass (e-commerce dropped manual masking); FLUX Kontext/Fill leads raw inpainting on complex masks (a selectable partner model in Photoshop Beta's Generative Fill); Firefly = licensed-training
- IP indemnification (the agency routing fact); Canva Magic tools for in-workflow fixes; Claid-class owns
product batches. Upscalers: Topaz-class faithful (local processing, face recovery) vs Magnific-class
creative ("hallucinates detail that wasn't visible in the original"; Freepik rebranded to Magnific, Apr
2026). Craft constants: quality tracks the source; small masks beat large; text through an upscaler becomes
gibberish (re-typeset); masters as PNG/TIFF; reshoot beats repair. Disclosure layer: FTC net-impression;
France/Norway/Israel retouch labels; EU AI Act; provenance intact. "The editing lane still rewards judgment
over blind automation." Attribute all; verify-quarterly. Full detail:
references/ai-image-editing-2026-reality.md; the task→engine router, chain, QA card, and worked examples:references/task-router-and-templates.md.
Show full SKILL.md (384 more words)Show less
Honest scope (never violate)
- The agent names the task, routes the engine, writes the spec (masks/prompts/settings/chain order), and calls APIs where connected (exact human steps otherwise); the human judges every result at 100% (no fabricated "the seams are clean"; the person who knew them judges a restored face); WoopSocial publishes the finished images — it does not edit, upscale, or remove backgrounds.
- The honesty spine: an edited real photo is an edited claim — no defect concealment, faithful upscaling for
accuracy-critical images, retouch-disclosure laws honored (verify per market), conservative face work,
consent for others' images, no watermark removal or provenance stripping, AI-disclosure where required,
source licenses confirmed. Never fabricate engine capabilities, benchmarks, or terms — test on your own
images; counsel for high-stakes claims. (Full scope:
references/scope-and-connections.md.)
Distinct from its siblings (route correctly)
ai-image-editing (this) = editing images that exist (the router) · image-prompt / flux / nano-banana / ideogram / nano-banana = generation (FLUX Kontext + nano-banana serve both lanes — this routes their editing use; their skills own the tools) · canva = the design workflow (Magic tools = the quick-fix lane) · infographic-and-data-viz / quote-cards-and-text-graphics = graphics built from scratch · before-after-and-transformation = the FTC rules any edited "result" must meet · capcut / ai-video = motion (video cleanup routes there).
Where this connects
Reads first: brand-profile + design-and-templates + before-after-and-transformation (results
imagery). Pulls sources from: real photography, flux/the generators (fixing generated images is half the
2026 workload), archives (restoration). Feeds: canva (edited assets into layouts), thumbnail-design /
carousel-writer / pinterest-pin-design, the platform publishing skills. Publishes via: master +
derivatives → scheduling-and-queue → WoopSocial. Tool file: tools/integrations/ai-image-editing.md.
Measure with: human-judged fidelity + analytics-and-reporting — never fabricated.
Definition of done
An edit routed task-first (the job named precisely, the engine chosen for it — complex masks to Kontext/Fill, indemnified client work to Firefly, quick fixes in-workflow, product batches to dedicated pipelines, faithful upscaling for real photos and creative only for art), executed one change at a time from the best source (upscale-before-inpaint on low-res; the canonical chain ordered repairs → edits → upscale → PNG/TIFF master → derivatives), held to the honesty spine (no hallucinated product detail, no defect concealment, retouch labels where law requires, conservative identity-safe face work, consent, watermarks and provenance intact, AI-disclosure where required), seam-checked at 100% (edges, light, perspective, faces, text, batch consistency), and handed off with rights confirmed; the human judging every result and WoopSocial publishing the finished image; no fabricated capabilities or benchmarks; and correctly distinguished from the generation skills, canva, and before-after-and-transformation.
© social-media-skills, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 5 other files (references) in skills/ai-image-editing of social-media-skills/skills.
- SKILL.md
- evals/evals.json
- references/ai-image-editing-2026-reality.md
- references/scope-and-connections.md
- references/task-router-and-templates.md
- references/the-touch-framework.md
Open the folder on GitHubat commit 6e30eeb
Compare with similar skills
AI Image Editing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| AI Image Editing this skillsocial-media-skills/skills | 134 | — | ~2.1k | Automated safety check: Pass | MIT | |
| AI Image Generation and Editingzhayujie/CowAgent | 47k | — | ~1.3k | Automated safety check: Pass | MIT | |
| BlockRun Image GenerationBlockRunAI/ClawRouter | 6.6k | — | ~2.1k | Automated safety check: Pass | MIT | |
| Antigravity Gemini ImageuluckyXH/OpenMOSS | 1.3k | — | ~730 | Automated safety check: Notes | MIT | |
| FigureMuuuun/luxas | 1.2k | — | ~1.2k | Automated safety check: Pass | MIT | |
| Gemini Image Generatordair-ai/dair-academy-plugins | 614 | 2 repos | ~3.5k | Automated safety check: Notes | MIT |
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uluckyXH/OpenMOSS
Generate or edit images using the Antigravity-hosted Gemini image model via the local gateway.
Figure
Muuuun/luxas
Hybrid figure pipeline (Nano Banana raster + rembg background removal + TikZ vector assembly).
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Generates and edits images with Google's Gemini Nano Banana Pro model through the Gemini API, including photo edits and multi-image composition.
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Related
Works with
Categories
Questions about AI Image Editing
What does AI Image Editing do?
The AI image-editing router — inpainting/object removal, background removal, upscaling, outpainting, old-photo restoration, and retouch, routed task-first to the right engine. AI Image Editing is an agent skill from social-media-skills/skills. The AI image-editing router — inpainting/object removal, background removal, upscaling, outpainting, old-photo restoration, and retouch, routed task-first to the right engine.
When should I use AI Image Editing?
AI Image Editing fits situations like: someone wants to remove an object/person from a photo; cut out backgrounds; upscale an image; extend an image to new aspect ratios.
How do I install AI Image Editing in Claude Code?
Run `npx skills add social-media-skills/skills --skill ai-image-editing -a claude-code`. Or copy the skill folder (skills/ai-image-editing in social-media-skills/skills) into .claude/skills/ai-image-editing in your project. Claude Code loads it when a task matches its description.
How do I install AI Image Editing in Codex?
Run `npx skills add social-media-skills/skills --skill ai-image-editing -a codex`. Or copy the skill folder (skills/ai-image-editing in social-media-skills/skills) into .agents/skills/ai-image-editing in your project. Codex loads it when a task matches its description.
Can I use AI Image Editing in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add social-media-skills/skills --skill ai-image-editing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-image-editing, .gemini/skills/ai-image-editing, .github/skills/ai-image-editing and .opencode/skills/ai-image-editing in your project.
What does AI Image Editing need to run?
SKILL.md names no scripts, command-line tools or credentials: AI Image Editing is instructions for the agent only.
Does AI Image Editing access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is AI Image Editing safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does AI Image Editing use?
AI Image Editing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does AI Image Editing use?
About 2.1k tokens (SKILL.md is roughly 8.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.4k tokens, read only when the agent opens those files.
What are the alternatives to AI Image Editing?
Skills that share tags, products or a category with AI Image Editing: AI Image Generation and Editing (zhayujie/CowAgent, 47k stars), BlockRun Image Generation (BlockRunAI/ClawRouter, 6.6k stars), Antigravity Gemini Image (uluckyXH/OpenMOSS, 1.3k stars) and Figure (Muuuun/luxas, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains AI Image Editing?
social-media-skills (a GitHub organization) maintains it in social-media-skills/skills, which has 134 GitHub stars. The repository holds 106 skills in this directory. The repository was last updated on October 1, 2026.
Source: social-media-skills/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.