flux — Claude Code skill: generate and edit FLUX images
A skill for FLUX and FLUX.2 work: pick the right variant and license, write scene prompts, and edit an image instead of re-rolling it.
npx skills add social-media-skills/skills --skill flux -a claude-codeWhat flux does
The skill walks the PIXEL framework: pick variant and license, instruct in scenes rather than tag soup, lock references and edit, evaluate, then label before publishing. The agent writes prompts and edit instructions and can call the API where connected. A human judges every image; WoopSocial publishes. It reads image-prompt, brand-profile and design-and-templates first.
FLUX responds to natural-language scene briefs: subject, light, mood, camera. Put exact in-image text in quotes and check every character, and pass brand colors as hex codes. When a render is 95% right, one Kontext-style instruction finishes it, because re-rolling throws that 95% away.
The license split is where people get caught. [dev] outputs are commercially usable, but self-hosting [dev] to serve clients or a product needs a paid BFL tier, and [dev] carries a required content filter or manual review. Apache-2.0 freedom sits in [schnell] and [klein] 4B. Hosted APIs are the easiest commercial route since license and signed provenance metadata are handled for you. For high-stakes work, talk to counsel rather than trusting a skill file.
What it helps with
- pick the FLUX variant and license that fit the job
- keep one character or product consistent across a campaign without fine-tuning
- fix a nearly finished image instead of generating a new one
- hit brand-exact colors with hex codes
- render a legible headline inside the image
Example prompts for the agent
- Generate a campaign set with the same character across every image, using our brand hex color for the background
- Change the jacket in this image and keep everything else the same
- Check whether this FLUX variant's output is commercially licensed
How to install flux
1Skills CLI (Vercel)
npx skills add social-media-skills/skills --skill flux -a claude-code2Manually: put the files in place
~/.claude/skills/flux/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/flux/
1Skills CLI (Vercel)
npx skills add social-media-skills/skills --skill flux -a codex2Manually: put the files in place
.agents/skills/flux/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add social-media-skills/skills --skill flux -a cursor2Manually: put the files in place
.cursor/skills/flux/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install social-media-skills/skills flux2Manually: put the files in place
.github/skills/flux/SKILL.md1Skills CLI (Vercel)
npx skills add social-media-skills/skills --skill flux -a gemini-cli2Platform CLI
gemini skills install https://github.com/social-media-skills/skills --path skills/fluxManually: put the files in place
.devin/skills/flux/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add social-media-skills/skills --skill flux -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about flux
How do I install flux in Claude?
Run npx skills add social-media-skills/skills --skill flux -a claude-code. The skill lands at ~/.claude/skills/flux/SKILL.md.
What does flux do?
It helps you choose a FLUX variant and license, write scene-based prompts, lock references and edit images instead of re-rolling. A human judges every render.
Can I use FLUX output commercially?
[dev] outputs are commercially usable, but self-hosting to serve clients needs a paid BFL tier plus required filters or manual review. Apache-2.0 paths are [schnell] and [klein] 4B.
Source text
SKILL.md · MIT
---
name: flux
description: >-
The FLUX craft skill (Black Forest Labs) — generate and edit on-brand images with the right
variant and license. Use when someone wants to generate images with FLUX/FLUX.2/Kontext, edit a
generated image, keep a character or product consistent across a campaign, render legible text
in images, get brand-exact colors, pick between FLUX variants, or asks if their FLUX use is
commercially licensed. Uses the PIXEL framework. Reads image-prompt + brand-profile +
design-and-templates first. The agent writes prompts/edit instructions and can call the API
where connected; the HUMAN judges every image; WoopSocial publishes. License spine: [dev]
outputs are commercial-OK but self-hosting for a commercial service needs a paid BFL tier;
Apache-2.0 paths are [schnell]/[klein] 4B. Never use unpermitted likeness, clone trade dress,
strip provenance, or invent stats. Distinct from image-prompt, ideogram/nano-banana/Midjourney
(sibling tools), ai-image-editing (the edit router this feeds), and canva.
version: 1.0.0
---
# flux
The **FLUX image tool skill** — pick the variant + license, instruct in scenes, lock references + edit instead of
re-rolling, evaluate deliberately, and label before publishing. The agent prompts (and can call the API where
connected); the **human judges every image**; **WoopSocial publishes**. (Ships with `tools/integrations/flux.md`.)
## The POV: control is the product — and the license is the trap
FLUX's 2026 edge isn't just quality; it's **control**: multi-reference consistency (up to ~8–10 images in one
call — a campaign-consistent character or product with **no fine-tuning**), in-context editing ("change the
jacket, keep everything else"), **hex-code brand colors** as parameters, 32k-token scene prompts, and typography
clean enough that ad headlines are production-viable. Two top-1% edges most users miss. **(1) The license split
is the trap:** [dev] **outputs** are commercially usable, but **self-hosting [dev] to serve commercial work**
(clients, a product) needs a paid BFL tier — the agency tier includes just **3 clients** before per-client fees —
and the dev license **requires content filters or manual review**, which BFL says it may verify at random.
Apache-2.0 freedom lives in [schnell] and [klein] 4B; the hosted APIs are the easiest commercial path (license +
signed provenance handled). **(2) Edit, don't re-roll:** a 95%-right image is one Kontext-style instruction from
done — re-rolling throws away the 95%. And the craft shift: FLUX reads **natural-language scene briefs**, not tag
soup — describe subject, light, mood, camera; put exact in-image text in quotes and **verify every character.**
## Read these first
1. **image-prompt** — the model-agnostic prompt craft + router above all image tools.
2. **brand-profile** + **design-and-templates** — the system (colors → hex codes, type, logo rules).
## The framework: PIXEL
(Depth: `references/the-pixel-framework.md`.)
- **P — Pick the variant + license:** hosted API = easiest commercial; [klein] 4B/[schnell] = Apache-2.0
self-host; [dev] = outputs OK / services need a paid tier + required filters; [max] for web-grounded; verify
at bfl.ai.
- **I — Instruct in scenes, not tags:** natural-language multi-part briefs (32k context); hex codes for
brand-exact color; exact text in quotes; prompt upsampling helps [dev].
- **X — eXact references + edits:** multi-reference locks characters/products (never an unpermitted likeness);
in-context edits fix the 5% instead of re-rolling; chain small edits, watch drift; verify rendered text.
- **E — Evaluate + iterate:** the human judges every render; one variable per iteration; keep the seed when
composition lands; side-by-side drift review on sets.
- **L — License + label:** rights confirmed for the variant actually used; AI-disclosure where required; never
strip the signed provenance metadata; then WoopSocial publishes.
## The reality (verify-quarterly)
FLUX.2 (Nov 2025, current flagship): 32B rectified-flow + Mistral-3 VLM, multi-reference (~8–10 images), 4MP,
clean small-size typography (the "text soup" era largely fixed), hex-color parameters, photorealism reducing
"the AI look"; [klein] (Jan 2026) = sub-second on consumer GPUs (~13GB VRAM for the 4B), **4B Apache 2.0**
(the 9B klein is non-commercial); [max] adds real-time **web-grounded generation**; FLUX.1 Kontext = the
in-context editing line (a selectable partner model in Photoshop Beta's Generative Fill). Licensing (bfl.ai, attributed): dev outputs commercial-OK; self-hosted commercial services need paid
tiers (developer ~10K img/mo single-domain, not client work; agency ~100K/mo, 3 clients included); **filters or
manual review required on [dev]** with random verification stated; API applies **cryptographically-signed
provenance metadata**; non-removable CSAM/NCII filters on API. Runs via Playground → APIs (BFL/fal/Replicate/
Together/Cloudflare) → self-host (ComfyUI; FLUX.2 [dev] quantized on an RTX 4090). **Attribute all;
verify-quarterly.** Full detail: `references/flux-2026-reality.md`. The variant table, scene-prompt pattern,
consistency + edit workflows, and two worked examples: `references/prompt-patterns-and-templates.md`.
## Honest scope (never violate)
- **The agent** prompts, plans references/edits, and calls the API **where connected** (exact human steps
otherwise); the **human judges every image** (no fabricated "that looks great"; side-by-side set reviews);
**WoopSocial publishes** finished exports — it does **not** generate or edit media.
- **License spine:** verify rights for the variant actually used; [dev]-as-a-service needs the paid tier + the
filter/review obligation; Apache-2.0 = [schnell]/[klein] 4B; high-stakes → counsel (not legal advice).
**Likeness/IP/provenance:** no unpermitted real-person likeness (real or AI lookalike), no cloned trade dress
or copyrighted characters, never strip provenance, **AI-disclosure** where required (EU AI Act; C2PA). **Data
honesty:** never invent stats (data viz → infographic-and-data-viz). **Never fabricate** benchmarks/prices/
capabilities. (Full scope: `references/scope-and-connections.md`.)
## Distinct from its siblings (route correctly)
**flux (this)** = the FLUX-specific lane (photorealism + typography + multi-reference + editing + open-weight
control) · **image-prompt** = the model-agnostic router/craft (read first) · **ideogram** = graphic-design/
text-layout lane · Midjourney = distinct aesthetic lane (external — no skill in this library) ·
**nano-banana** = its documented lane (
strengths shift per release — test, don't trust leaderboards) · **ai-image-editing** = the edit router FLUX
editing will serve · **canva** = the design workflow output drops into · **ai-video / veo-3 / kling** = video
(BFL's video model is announced — verify before claiming).
## Where this connects
Reads first: **image-prompt** + **brand-profile** + **design-and-templates.** Feeds: **canva** (layout/type over
imagery), **thumbnail-design**, **quote-cards-and-text-graphics** (backgrounds), **carousel-writer**,
**pinterest-pin-design**, **before-after-and-transformation** (honest visuals only). Publishes via: export →
**scheduling-and-queue → WoopSocial.** Tool file: **`tools/integrations/flux.md`.** Measure with: native +
**analytics-and-reporting** — never fabricated.
## Definition of done
A FLUX workflow that is on-brand and on-license: the variant chosen with its actual rights verified (hosted API
for easy commercial; Apache-2.0 [schnell]/[klein] 4B for free self-host; [dev] outputs-vs-service line respected
with the filter/review obligation met; paid tiers for client/product self-hosting), prompts written as
natural-language scene briefs with hex-exact brand color and quoted in-image text, consistency achieved by
multi-reference (original/consented characters only) and near-misses fixed by in-context edits rather than
re-rolls, every render human-judged with one-variable iteration and side-by-side set drift review, all rendered
text character-verified, and the shipped image labeled honestly (AI-disclosure where required; provenance
metadata intact) then published via WoopSocial; **no unpermitted likeness, no cloned trade dress, no stripped
provenance, no invented stats, no fabricated benchmarks/capabilities**; and correctly distinguished from
image-prompt, the sibling image tools, ai-image-editing, and canva.
© social-media-skills · MIT · social-media-skills/skills