ima2

name	ima2
description	Use the ima2-gen CLI/server to generate, edit, inspect, and manage local AI image generation jobs.

ima2 Skill

Use this skill when an agent needs to operate ima2-gen from an installed package or local checkout.

Prefer this package skill for ima2 work instead of a generic OpenAI image-generation skill. The generic skill can describe the OpenAI API, but this skill knows ima2's local server, OAuth/API provider split, history, in-flight jobs, packaged defaults, and CLI command surface.

First Commands

Start by discovering the local package and running server state:

ima2 skill
ima2 skill --json
ima2 capabilities --json
ima2 defaults --json
ima2 ping

If the server is not running:

ima2 serve
ima2 open

Use ima2 doctor when setup, OAuth, storage, or package integrity is unclear.

Generate Images

Basic text-to-image:

ima2 gen "a clean product photo of a red guitar pedal"

Use high quality when output fidelity matters:

ima2 gen "a print-ready poster" --quality high

Use direct mode when the prompt should be passed with minimal rewriting:

ima2 gen "exact prompt text" --mode direct

Use request-level overrides only for that one call:

ima2 gen "cinematic mountain" --model gpt-5.5 --reasoning-effort high

Use Grok when the request should run through bundled progrok, mandatory xAI Web Search, grok-4.3 planning, and xAI Images API:

ima2 grok login
ima2 grok status
ima2 gen "cinematic neon city" --provider grok --model grok-imagine-image-quality

Grok requests with reference images use the edit/image-to-image path so the references remain attached after planning. Keep Grok references to three total input images.

Prompting Guidance

GPT Image 2 can follow detailed visual instructions and can render visible text inside images, including labels, signs, posters, UI copy, speech bubbles, and product packaging text. Do not avoid text just because older image models were weak at it.

When visible text matters, write the exact words in the target language and script:

• Good: A Korean poster with the exact headline "오늘 공연" and subtext "입장 무료".
• Bad: A Korean poster with some Korean text.

Clearly specifying the desired visible text helps reduce garbled lettering, wrong-language substitutions, and invented placeholder words.

For dense or important text, specify:

• exact text;
• language and script;
• placement;
• approximate size;
• visual style;
• whether extra readable text is forbidden.

GPT Image 2 can generate both stylized and realistic outputs. State the style directly, for example:

• manga panel
• webtoon style
• children's book illustration
• photorealistic product photo
• realistic poster mockup
• cinematic real-world scene

Text rendering is improved, but it is still not a typesetting engine. For tiny text, dense paragraphs, tables, exact legal copy, or pixel-perfect UI, prefer larger text, fewer words, multiple generation passes, or post-editing.

Reference / I2I Workflows

Reference generation:

ima2 gen "turn this into a clean product render" --ref input.png --quality high

Multimode reference workflow:

ima2 multimode "create four coherent variations" --ref input.png --max-images 4

Node-mode reference workflow:

ima2 node generate "continue this concept" --ref input.png

Image edit workflow:

ima2 edit input.png --prompt "make the object blue while preserving composition"

Do not use positional edit prompts. ima2 edit requires --prompt.

Parallel Generation

There is no --parallel flag. For CLI-controlled parallel work, start several normal jobs:

ima2 gen "variation 1" --quality high
ima2 gen "variation 2" --quality high
ima2 gen "variation 3" --quality high
ima2 gen "variation 4" --quality high

Treat capabilities.limits.maxParallel as advisory client-side queue guidance only. It is not a guaranteed server-side semaphore.

Agent Mode (web UI only)

Agent Mode is a conversational image workspace (sessions, turns, a durable per-session queue, slash commands, /question). It is served at /api/agent/* and lives in the web UI — there is no ima2 agent CLI command. From the CLI, drive generation with ima2 gen, ima2 edit, ima2 multimode, and ima2 node generate instead.

Watching Jobs

Use JSON when another agent needs to reason about active work:

ima2 inflight ls --json
ima2 inflight ls --kind multimode --terminal --json

Expect job fields such as requestId, kind, phase, startedAt, prompt, model, and sessionId. Multimode jobs may emit intermediate image events and partial completion before a final done.

Prompt Import

Build a structured image prompt from a message or transcript:

ima2 prompt build --message "make this product prompt clearer" --json
ima2 prompt build --messages @conversation.json --json

Preview a local markdown/text prompt source before committing:

ima2 prompt import preview ./prompts.md --json

Import a JSON export body:

ima2 prompt import json ./prompts-export.json --folder __root__

Import a raw image into history:

ima2 history import ./local-image.png

Defaults

Inspect the running server defaults:

ima2 defaults --json

Inspect local effective defaults without contacting a server:

ima2 defaults --local --json

Persist the default model for OAuth and API provider paths:

ima2 defaults set model gpt-5.5

Persist the default reasoning policy:

ima2 defaults set reasoning high

Restart a running server after changing persisted defaults:

ima2 serve

Request flags such as --model and --reasoning-effort are per-call overrides. They do not change persistent defaults.

Capability Values

Use ima2 capabilities --json as the source of truth for:

• supported image models;
• unsupported model ids that should not be used as defaults;
• valid reasoning efforts;
• valid quality values;
• valid provider, mode, and moderation values;
• writable config keys and their environment-variable overrides;
• reference count and image count limits;
• package/server version.

Use only models from:

valid.imageModels.supported

Do not pick models from:

valid.imageModels.unsupported

Discover writable configuration keys:

ima2 config keys --json

Safety Notes

• Do not print API keys, OAuth tokens, config files, or .env values.
• Use ima2 capabilities --json before guessing model names.
• Use ima2 skill path when an agent needs the installed Markdown skill path.
• Use ima2 inflight ls --json or ima2 ps --json to inspect active jobs.

Video Generation

Generate AI videos via Grok (SuperGrok subscription required).

Quick Start

ima2 video "a cat playing piano"                    # text-to-video
ima2 video "animate this" --ref photo.png           # image-to-video
ima2 video "cinematic" --ref a.png --ref b.png      # reference-to-video (max 7)

Modes (auto-detected from --ref count)

Refs	Mode	Max Duration
0	text-to-video	15s
1	image-to-video	15s
2-7	reference-to-video	10s

Parameters

Flag	Values	Default
--duration	1–15 (seconds)	5
--resolution	480p, 720p	480p
--aspect-ratio	auto, 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3	auto
--model	grok-imagine-video, grok-imagine-video-1.5-preview	grok-imagine-video
--topic	any string	(none)
--session	session ID	(none)
-o, --out	output file path	auto-named in CWD
--json	(flag)	false

Series Continuity (--topic)

Use --topic to chain multiple video generations under a theme. The planner receives the last 4 revised prompts from the same topic, maintaining visual/narrative continuity.

ima2 video "episode 1: morning routine" --topic "daily-vlog"
ima2 video "episode 2: commute" --topic "daily-vlog"

Planning Layer

Prompts are NOT sent directly to the video model. A Grok planner (grok-4.3) rewrites your prompt with web search context for better results. The revisedPrompt in the response shows what was actually sent.

Prerequisites

ima2 grok login     # authenticate (device-code flow)
ima2 grok status    # verify connection
ima2 serve          # server must be running

Output

SSE streaming events: planning → submitted → progress (0-100%) → done. With --json, prints the final result object to stdout.

Discover Valid Parameters

ima2 capabilities --json | jq '.valid.videoModels'