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Ai Image Editing

skill-social-media-skills-skills-ai-image-editing · by social-media-skills

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Install

$ agentstack add skill-social-media-skills-skills-ai-image-editing

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

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

  1. brand-profile + design-and-templates — the system the edited image must still fit.
  2. 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.

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.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.