- name
SKILL.md
Die Skill-Datei bleibt im Repository des Herausgebers.
Fügen Sie den kopierten Befehl in ein Terminal ein. Er installiert diese SKILL.md in dem jeweiligen Agenten.
npx skills add digitalsamba/claude-code-video-toolkit --skill ideogram4 -a cursor -yFügen Sie den kopierten Befehl in ein Terminal ein. Er installiert diese SKILL.md in dem jeweiligen Agenten.
npx skills add digitalsamba/claude-code-video-toolkit --skill ideogram4 -a claude-code -yFügen Sie den kopierten Befehl in ein Terminal ein. Er installiert diese SKILL.md in dem jeweiligen Agenten.
npx skills add digitalsamba/claude-code-video-toolkit --skill ideogram4 -a codex -yFügen Sie den kopierten Befehl in ein Terminal ein. Er installiert diese SKILL.md in dem jeweiligen Agenten.
npx skills add digitalsamba/claude-code-video-toolkit --skill ideogram4 -a grok -ySenden Sie die kopierte Nachricht in einem Grok Bot-Chat. Der Bot ruft diese SKILL.md von GitHub ab und fügt sie den Skills hinzu, die alle Ihre Bots gemeinsam nutzen.
Install this skill: https://github.com/digitalsamba/claude-code-video-toolkit/tree/HEAD/.claude/skills/ideogram4Vom Herausgeber
Text-to-image generation with Ideogram 4 (9.3B, open-weight, released June 2026). Its superpower is best-in-class in-image text rendering — it beats much larger models (FLUX.2 dev 32B, Qwen-Image 20B, Hunyuan 80B) at rendering legible signage, logos, captions, and multi-line text — plus exact color-palette and bounding-box control.
That advantage is locked behind a structured JSON caption format. A plain-text prompt gets you FLUX-level results and misses the entire point of using this model. This skill teaches Claude to act as the "magic prompt" expander — turning a user's casual request into the JSON caption Ideogram 4 was trained on.
Backend: The toolkit uses Ideogram's hosted v4 API (not self-hosted weights). The API accepts a structured
json_prompt, so everything this skill teaches applies directly — Claude builds the caption, the tool posts it asjson_prompt. Paid API plans include a commercial license, which the self-hostable weights (non-commercial) do not — that's why we use the API. Cost is ~$0.03/image (turbo) to ~$0.10/image (quality).
Reach for Ideogram 4 (over FLUX.2) when the image needs:
Use FLUX.2 instead when: the image has no critical text, you need commercial-licensed output,
or you just want a fast atmospheric background. FLUX takes plain natural-language prompts; Ideogram
wants JSON. See tools/flux2.py.
Always emit a structured JSON caption, not a plain sentence. The model is trained exclusively on JSON captions that name every element explicitly. Claude is a better expander than Ideogram's free hosted magic-prompt (their own docs note the shipped one "is not the same used in production"), so build the caption yourself using this skill rather than passing raw text.
Minimal valid caption:
{"high_level_description":"A sailboat at sunset on calm water.","style_description":{"aesthetics":"serene, warm, golden hour","lighting":"golden hour backlighting","photo":"wide angle, f/8","medium":"photograph","color_palette":["#FF6B35","#F7C59F","#004E89"]},"compositional_deconstruction":{"background":"Calm ocean at low horizon with orange-pink sky.","elements":[{"type":"obj","desc":"White triangular sail silhouetted against the setting sun."}]}}
Full schema, strict key-ordering rules, and the bbox coordinate system are in prompting.md.
Worked title-card / thumbnail / quote-card examples are in examples.md.
tools/ideogram4.pyThin wrapper over Ideogram's hosted v4 API. Needs
IDEOGRAM_API_KEYin.env(key from developer.ideogram.ai).--jsonposts the caption as the API'sjson_promptfield (no server-side magic prompt — Claude is the expander);--promptpoststext_prompt.
# Hand-authored JSON caption (the recommended path for text/layout) — Claude writes caption.json
uv run tools/ideogram4.py --json caption.json --output title.png
# Caption from stdin (Claude can pipe it directly)
cat caption.json | uv run tools/ideogram4.py --json - --output title.png
# Plain prompt — Ideogram's server-side magic prompt expands it (weaker; prefer --json)
uv run tools/ideogram4.py --prompt "Title card: 'AI ENGINEERING REVIEW' bold white on dark" --output title.png
# Inject brand hex colors into the caption's palette (JSON mode)
uv run tools/ideogram4.py --json caption.json --brand digital-samba --output cta.png
# Quality tier + resolution
uv run tools/ideogram4.py --json caption.json --speed QUALITY --resolution 2048x2048 --output slide.png
--model 4.5 sends the same flags to Ideogram 4.5 on the v2 API
(POST /v2/image/generate/ideogram-4-5, multipart like the v1 call). It has been run live:
JSON captions render near-perfect text; plain prompts add garbled filler text, so always
send a JSON caption to 4.5. Ideogram 4 stays the default because 4.5 sizes must be multiples
of 32, which rules out exact YouTube 1280x720 (/thumbnail uses 4.0 for that).
uv run tools/ideogram4.py --model 4.5 --json caption.json --speed QUALITY --resolution 1440x2560 --output card.png
Prompt: both modes go in 4.5's single prompt field. --json sends the caption as
compact JSON. 4.5 reads the Ideogram 4 caption format, and a valid caption skips
server-side magic prompt. --prompt text is expanded by magic prompt, as on v1.
--speed maps to quality: TURBO, DEFAULT and QUALITY at the same price as on
Ideogram 4, and FLASH, which has no Ideogram 4 price, to low (Ideogram's list prices,
checked 2026-10-12; 1K and 2K sizes cost the same):
4.5's very_low tier needs source images, so the tool never sends it. On --model 4,
FLASH is still sent as is, but Ideogram's docs say it currently returns HTTP 400.
--resolution is sent as size: auto, or WIDTHxHEIGHT with both sides multiples of
32 and at least 256px, at most 2048x2048 pixels in total, and an aspect ratio of at most
6:1. Omit it and Ideogram picks a size from the prompt. The tool checks these rules before
calling the API and exits 2 when a size breaks them. 1440x2560 (the 9:16 card size) and
2048x2048 pass. Six Ideogram 4 presets don't, and the error suggests a replacement:
720x1280 (1440x2560), 1280x720 (2560x1440), 720x1440 (1440x2880), 1440x720 (2880x1440),
1296x3168 (1280x3072), 3168x1296 (3072x1280). Without source images Ideogram also needs
one of its supported 1K/2K presets, a list it doesn't publish, so a size that passes the
checks can still get an HTTP 400.
prompting.md — full JSON schema, strict key ordering, bbox coordinate system, palette rulesexamples.md — worked captions for title cards, thumbnails, quote cards, brand CTAsIdeogram 4's niche in the toolkit is slides and thumbnails with baked-in text, where FLUX and LTX-2 fail (both render garbled text). Natural pairings:
Then feed the still into Remotion (<OffthreadVideo>/Img) or animate it with tools/ltx2.py --input.
Prompting patterns for Ideogram 4 text-to-image — best-in-class in-image text rendering and exact color/layout control via structured JSON captions. Use when generating images that need legible on-ima
---name: ideogram4description: Prompting patterns for Ideogram 4 text-to-image — best-in-class in-image text rendering and exact color/layout…---# .claude/skills/ideogram4/SKILL.mdÜbersicht
Prompting patterns for Ideogram 4 text-to-image — best-in-class in-image text rendering and exact color/layout control via structured JSON captions. Use when generating images that need legible on-image text (title cards, thumbnails, logos, signage, CTAs), precise brand colors, or controlled spatial layout. Triggers include title slide image, thumbnail with text, on-image text, legible text in image, brand color palette image, bounding-box layout, Ideogram.
FAQ
Laden Sie .claude/skills/ideogram4/SKILL.md vom Herausgeber herunter oder kopieren Sie den Pfad und öffnen Sie das Repository. PlugMCP listet den Skill und hostet die Datei nicht.
Der Herausgeber pflegt es unter https://github.com/digitalsamba/claude-code-video-toolkit.
Claude, Cursor, Codex und Grok Build können eine SKILL.md lesen, die Sie aus dem Repository des Herausgebers hinzufügen. Grok Bot installiert sie, wenn Sie den Link zum GitHub-Ordner des Skills in einem Chat senden.