p-image-ideogram

Use when photo generation needs more control — photoreal results, text in the image, or structured JSON with hex colors and bounding boxes. Simpler photo generation, edits, and video use other skills in the suite.

Prerequisites

Install and load these skills before generating (skip if already in context via @pruna):

Skill	Description	Install
generation-diversity	Use when writing any generative prompt — ritual seed, explicit structure, scenario axes, and quality gates before paid API calls.	npx skills add PrunaAI/pruna-skills@generation-diversity -y
image-prompting	Use when crafting still-image prompts for any generative model — composition, identity sheets, edits, try-on, and photoreal personas.	npx skills add PrunaAI/pruna-skills@image-prompting -y
pruna-api	Use before any Pruna or Replicate HTTP call — credentials, upload/poll/download, parallel batches, and agent safety.	npx skills add PrunaAI/pruna-skills@pruna-api -y

Or install the full suite once: npx skills add PrunaAI/pruna-skills@pruna -y

Follow each skill's Before generating / craft sections — do not restate guide content here.

Agent habit

Route by complexity: Use `p-image-ideogram` when photo generation needs more control — readable text in the image, structured JSON, hex/bbox placement, or high-detail photoreal shots. Use `p-image` for simple, quick photo generation. Use `p-image-edit` to change an existing photo; use `p-video-2` (`p-video-animate` from a still) for motion.

In the first reply, name `p-image-ideogram` in backticks, confirm PRUNA_API_KEY is set (or stop with signup links from pruna-api), then ask for prompt / aspect ratio / any copy-on-surface (open intake → generation-diversity clarification intake). When drafting the prompt, follow Prompt craft below — do not paste skill examples.

Agent defaults (override API defaults): send thinking: "high", prompt_upsampling: true, and image_size: "1K" unless a profile in domain-configurations.md says otherwise. Use image_size: "2K" for dense in-image text, multi-panel layouts, and large output. Set prompt_upsampling: false when text is locked (JSON prompts, exact strings) or the user wants verbatim prompts only.

Premium path: when the user requests maximum quality or the composition is highly complex (many text elements, intricate multi-panel layouts, detailed structured scenes), send thinking: "very high" + image_size: "2K". Costs ~2× high ($0.033/1K, $0.066/2K) — confirm with the user before using unless they explicitly asked for top quality.

Speed path (same model): when the scene is simpler but you still want ideogram (or need a faster pass on this model), send thinking: "low", prompt_upsampling: false, and a nuanced, explicit prompt you fully draft — upsampling stays off because the prompt already carries the detail. Faster than the default high + upsampling path. For the simplest quick photo drafts, route to p-image instead.

When the job comes from a vertical-* workflow (or another multi-step production with spec copy or covers), pick thinking, image_size, and NL vs JSON from domain-configurations.md for that vertical and use-case # — do not use one global knob set for every industry.

vs p-image

	`p-image-ideogram`	`p-image`
When	More control — text in the image, JSON layout, hex/bbox, detailed photoreal photos	Simple, quick photo generation from a short prompt
Quality	Strong photorealism and typography; five thinking levels (very low to very high); 1K / 2K	Good quality, extremely fast; no prompt upsampling
Prompt upsampling	true by default (high path); false on speed path or locked copy / JSON	None — concrete language is the whole craft
Knob default	thinking: high + prompt_upsampling: true	Single fast pass — no thinking/upsampling knobs
Structured layout	Ideogram 4.0 JSON caption in prompt (hex, bbox, "text" elements) — see ideogram-json-prompting.md	Avoid dense readable type

Official parameters: P-Image-Ideogram

Prompt craft (dynamic + faithful)

Every input.prompt must be fresh and specific, and must keep the user's request. Diversity never overrides what the user asked for.

Do	Don't
Run the generation-diversity random seed ritual; state it; rotate ≥2 free axes (camera, lighting, setting texture, render category)	Copy curl examples from this skill or reuse a prior session's prompt verbatim
Lock user-required facts first (subject, product, brand cues, must-keep props, exact strings for text in the image)	Swap the subject for a “cooler” scene that ignores the request
For structured layouts, use the Ideogram JSON caption schema in input.prompt when placement, palette, or repeatability matter; otherwise name panels, literal copy, and hex in natural language	Chain p-image-edit to fix multi-panel copy — regenerate the photo instead
Expand with concrete nouns, frozen action, materials, placement (image-prompting golden rules)	Vague mood-only strings (cool product vibe, neon)
Show drafted prompt + thinking + image_size + aspect_ratio + prompt_upsampling before POST when the user has not locked wording	Silent regen with a different subject than approved

Fidelity check (before pay): if you remove the user’s named subject/product/setting from the prompt, the job is wrong — rewrite. Free axes only fill what the user did not specify.

Typography: list every string and surface; use image_size: "2K" and prompt_upsampling: false when legibility is critical (default thinking: "high"). Domain-specific profiles and vertical rows: domain-configurations.md. JSON captions (exact placement, brand hex, repeatable layout): ideogram-json-prompting.md.

Thinking & resolution

thinking	Best for
very low	Basic photos, fastest ideogram pass
low	Speed path — pair with prompt_upsampling: false and a nuanced explicit prompt; faster than the default when the scene is simpler but ideogram is still the right model
medium	Middle ground when high is heavier than needed but the prompt is not fully self-contained
high	Default agent choice — text in the image, multi-panel layouts, editorial portraits; pair with image_size: "2K" when legibility or large output matters
very high	Maximum quality — complex compositions with multiple text elements, intricate layouts, or when the absolute best output justifies the ~2× cost over high; pair with image_size: "2K" for best results

When NOT to use

Use a different skill instead:

Skill	Description	Install
p-image	Use when someone explicitly wants the fastest, cheapest photo generation — mood boards, bulk panels, or quick iterations — not when controlled photoreal or in-image text is needed.	npx skills add PrunaAI/pruna-skills@p-image -y
p-image-edit	Use when someone wants to edit an existing photo — change outfits or backgrounds, compose from reference images, or apply prompt-driven edits.	npx skills add PrunaAI/pruna-skills@p-image-edit -y
p-image-try-on	Use when someone wants virtual try-on — dress a person in clothes from reference photos for fashion or ecommerce.	npx skills add PrunaAI/pruna-skills@p-image-try-on -y

HTTP (curl)

Create (async — recommended)

bash

curl -X POST 'https://api.pruna.ai/v1/predictions' \
  -H 'Content-Type: application/json' \
  -H "apikey: ${PRUNA_API_KEY}" \
  -H 'Model: p-image-ideogram' \
  -d '{
    "input": {
      "prompt": "South Asian woman founder mid-30s, documentary portrait at cast-iron loft window, natural skin pores, mouth visible, hands away from mouth, golden hour side light, photoreal editorial",
      "thinking": "high",
      "image_size": "1K",
      "prompt_upsampling": true,
      "aspect_ratio": "9:16"
    }
  }'

Poll and download: follow pruna-api.

Complete the random seed ritual from generation-diversity before writing prompts — do not pass the ritual string as API seed. Optional seed only when the user requests reproducibility.

Create (sync — quick test only)

bash

curl -X POST 'https://api.pruna.ai/v1/predictions' \
  -H 'Content-Type: application/json' \
  -H "apikey: ${PRUNA_API_KEY}" \
  -H 'Model: p-image-ideogram' \
  -H 'Try-Sync: true' \
  -d '{"input":{"prompt":"Hong Kong neon alley at night, fearless grandmother in floral apron juggling dumplings, awning reads HAPPY HOUR 5-7, kiosk sign PRUNA AI, fish-eye lens, crisp legible typography","thinking":"high","image_size":"2K","prompt_upsampling":true,"aspect_ratio":"9:16"}}'

Generation flow

Follow generation-diversity still-image prompt flow every time:

1. Lock the request — subject, product, format, any text on the image.
2. Ritual seed — fresh string; derive free axes (camera, lighting, render_category_tag, aspect_ratio when unset).
3. Pick knobs — domain-configurations.md profile for the vertical/use case, else default thinking: high, image_size: 1K, prompt_upsampling: true; or speed path — thinking: low, prompt_upsampling: false, nuanced explicit prompt; or premium path — thinking: "very high", image_size: "2K" for maximum quality on complex compositions; raise image_size to 2K for dense in-image text or multi-panel layouts; set prompt_upsampling: false for locked text or JSON.
4. Draft explicit prompt — Prompt craft + image-prompting golden rules; fidelity check before pay.
5. Confirm — show prompt + knobs unless wording is locked.
6. POST — async curl below; poll via pruna-api; run p-image quality checklist in image-prompting before upscale/video.

Aspect ratio: pass aspect_ratio in input; if output dimensions do not match (e.g. asked 16:9, got portrait), retry once with explicit horizontal wide / vertical wording in the prompt.

Mood board / batch: new ritual per independent photo; different aspect_ratio per panel when format not locked.

Photo approved → edit: hand off to p-image-edit on the output URL for photo edits — do not run photo generation again for the same subject; do not use edit to fix dense multi-panel in-image text (regenerate instead).

Photo approved → video: use p-video (image-to-video) or p-video-animate when motion is next; upscale first with p-image-upscale if resolution is tight.

Required input

• prompt (string)

Common optional fields

• thinking: very low, low, medium, high, very high — default high; low + prompt_upsampling: false + explicit prompt for the speed path; very high for maximum quality on complex compositions
• image_size: 1K, 2K (ignored when aspect_ratio is custom)
• prompt_upsampling: boolean — default true with thinking: high; false on speed path, locked copy, JSON prompts, or verbatim wording
• aspect_ratio: 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, custom (with width / height up to 2560, multiples of 16)
• seed, output_format (jpg, png, webp), output_quality (0–100; ignored for png)

Typical next steps

Common follow-ons after this skill:

Skill	Description	Install
p-image-edit	Use when someone wants to edit an existing photo — change outfits or backgrounds, compose from reference images, or apply prompt-driven edits.	npx skills add PrunaAI/pruna-skills@p-image-edit -y
p-image-try-on	Use when someone wants virtual try-on — dress a person in clothes from reference photos for fashion or ecommerce.	npx skills add PrunaAI/pruna-skills@p-image-try-on -y
p-image-upscale	Use when someone wants to upscale or sharpen an existing image for print, large crops, or higher-quality delivery.	npx skills add PrunaAI/pruna-skills@p-image-upscale -y
p-video	Use when someone wants a simple short clip from text or images — quick B-roll, drafts, or start/end frame animation. Not when the brief needs the highest quality or tight lip-sync.	npx skills add PrunaAI/pruna-skills@p-video -y
p-video-avatar	Use when someone wants a person on camera speaking a script — lip-synced host, spokesperson, or narrated avatar from a portrait photo.	npx skills add PrunaAI/pruna-skills@p-video-avatar -y