Auto Midjourney

Auto Midjourney

Use the user's own Midjourney Alpha web session to submit imagine jobs and optionally poll for results.

This skill is intended for conservative, user-triggered assistance rather than unattended bulk automation.

What this skill does

• Submits prompts to https://alpha.midjourney.com/api/submit-jobs
• Defaults to Midjourney v8 for new prompts unless the user explicitly requests another version
• Keeps credentials in environment variables instead of hardcoding them into the skill
• Supports a one-command flow through scripts/run_imagine.py
• Can read https://alpha.midjourney.com/api/user-mutable-state to inspect current web settings
• Can infer user_id and singleplayer_<midjourney_id> from the authenticated cookie
• Applies local conservative throttling to reduce accidental request bursts
• Includes scripts/mj_doctor.py for setup validation
• Includes an experimental recent-jobs reader
• Supports browser transport backed by Chrome DevTools Protocol, with Playwright-over-CDP preferred when installed
• Supports optional polling once a job-status endpoint has been confirmed
• Includes prompt-craft guidance and reusable scenario presets for better prompt writing
• Includes a structured prompt builder and opt-in quality profiles
• Includes dedicated guidance for character sheets, split-view turnarounds, and reusable design assets

Current scope

This version focuses on:

1. imagine
2. Midjourney v8 as the default version
3. Alpha web flow, not Discord bot flow
4. Safe local configuration via .env
5. Easier operation through inferred IDs, presets, and doctor checks

Implemented:

• imagine submit through the Alpha web flow
• browser-backed verification using low-impact CDP network watching plus page asset fallback
• local download of the 4 returned image assets
• optional browser-side conversion from webp to png during download
• sequential batch generation

Not implemented yet:

• Upscale / variation / reroll button actions
• Image upload / reference-image workflow
• Automatic result download from a confirmed final image endpoint

Those should be added only after capturing stable request samples from the browser.

Safety posture

Do not optimize this skill for bypassing restrictions, hiding automation, rotating accounts, or mass unattended generation.

Use these guardrails instead:

• trigger requests manually
• keep request frequency low
• leave local throttling enabled
• validate config with mj_doctor.py
• prefer one human action to one live submit

The goal is risk reduction through conservative usage, not evasion.

Trigger rules

Use this skill proactively when the user asks to:

• “用 Midjourney / MJ 出图”
• “用 Midjourney v8 生成”
• “帮我提交 imagine”
• “优化 Midjourney prompt”
• “做角色设定稿 / 四视图 / 角色资产图”
• “抓 Midjourney Alpha 网站请求”
• “轮询 Midjourney job 状态”
• “把网页版 Midjourney 做成自动化能力”

Required configuration

Read these values from .env or shell environment:

Never write real cookies or tokens into SKILL.md, reference files, git-tracked scripts, or user-facing summaries.

System requirements

For platform and device requirements, read system-requirements.md.

Workflow

Scenario 0: Check config first

Run:

python3 scripts/mj_doctor.py --fetch-user-state --transport browser

This shows:

• whether the cookie exists
• inferred midjourney_id
• inferred channel_id
• current server-side speed and visibility
• current local safe-limit settings

Scenario 1: Submit one prompt

Run:

python3 scripts/run_imagine.py "1 girl --ar 16:9" --transport browser

Default behavior:

• Appends --v 8 if the prompt does not already specify a version
• Appends --raw by default unless the user disables it
• Uses MJ_MODE and MJ_PRIVATE from the environment
• Can sync server-side defaults before submitting
• Records the submit locally and enforces conservative pacing
• Prints structured JSON with the request payload, submission response, and extracted job_id

For simplest live use:

python3 scripts/run_imagine.py "cinematic portrait of a fox astronaut" --transport browser --sync-user-state --wait-page-assets --download --convert-to png

When --wait-page-assets is enabled, the browser transport now prefers watching Midjourney's existing in-page network traffic for the submitted job_id. It falls back to page asset probing only if the low-impact watcher does not yield 4 images.

Scenario 2: Submit and wait

If a working status endpoint has been captured and stored in MJ_STATUS_URL_TEMPLATE, run:

python3 scripts/run_imagine.py "cinematic portrait of a fox astronaut --ar 16:9" --wait

Scenario 3: Low-risk debugging

Use dry-run first when changing payload structure:

python3 scripts/run_imagine.py "robot barista in tokyo alley" --dry-run

This validates prompt normalization and payload generation without sending a live request.

Scenario 3b: Use a preset

Run:

python3 scripts/run_imagine.py "silver perfume bottle on black glass" --preset product --sync-user-state

Preset definitions live in config/presets.example.json.

When the user wants better prompt wording, templates, or parameter tradeoffs, read prompt-craft.md.

Scenario 3c: Build a prompt from a template

Run:

python3 scripts/mj_prompt_helper.py --template product --subject "premium silver perfume bottle" --camera "front three-quarter angle" --surface "black glass surface" --lighting "controlled softbox rim light" --background "dark charcoal background" --mood "minimal luxury beauty campaign" --preset product_clean_square --quality-profile final_v8_q4 --json

This produces a V8-friendly prompt string and a ready-to-run run_imagine.py command.

Scenario 4: Read current web settings

Run:

python3 scripts/get_user_state.py --transport browser

This reads the same user-mutable-state endpoint the web app uses and returns values such as:

• settings.speed
• settings.visibility
• abilities
• saved macros

Command reference

Submit only

python3 scripts/submit_job.py "minimalist glass monolith --ar 16:9 --v 8"

Poll one job

python3 scripts/poll_job.py "<job_id>"

Inspect current server-side settings

python3 scripts/get_user_state.py --transport browser

Validate config and inferred identity

python3 scripts/mj_doctor.py --fetch-user-state --transport browser

Experimental recent jobs lookup

python3 scripts/list_recent_jobs.py --amount 10

Submit, verify, and download locally

python3 scripts/run_imagine.py "fashion editorial, silver fabric, studio light --ar 3:4" --transport browser --sync-user-state --wait-page-assets --download --convert-to png

Batch generate and store PNGs

python3 scripts/batch_generate.py config/prompts.example.txt --transport browser --sync-user-state --convert-to png

Use conservative fixed spacing and batch cooldowns when needed:

python3 scripts/batch_generate.py config/prompts.example.txt --transport browser --sync-user-state --convert-to png --batch-size 5 --submit-interval-seconds 120 --batch-cooldown-seconds 600

Apply an opt-in quality profile to the whole batch:

python3 scripts/batch_generate.py config/prompts.example.txt --transport browser --sync-user-state --quality-profile final_v8_q4 --convert-to png

Convert existing WEBP downloads to PNG

python3 scripts/convert_downloads.py outputs

Or write converted files into a separate directory:

python3 scripts/convert_downloads.py outputs --output-dir outputs/png-converted

If you want to rebuild PNGs from a saved result manifest instead of local files:

python3 scripts/convert_downloads.py outputs/live-test/recent-job.json --output-dir outputs/png-rebuilt

This waits for the submitted job_id to appear in the browser page resource list, verifies that 4 Midjourney CDN image URLs exist, and downloads the returned image files into outputs/<job_id>/.

Batch generate sequentially

Create a text file with one prompt per line, then run:

python3 scripts/batch_generate.py prompts.txt --transport browser --sync-user-state --download-dir outputs/batch

This submits prompts one by one, waits for each job_id to produce page resource URLs, and downloads the returned image files before moving to the next prompt.

Full flow

python3 scripts/run_imagine.py "fashion editorial, silver fabric, studio light --ar 3:4" --sync-user-state --wait-recent-jobs --download

Prompt defaults

When the user does not specify MJ flags:

• Default to --v 8
• Default to --raw
• Preserve any explicit aspect ratio or style flags already present
• Do not auto-add --hd
• Treat --q 4 as an opt-in final-pass override rather than a default for the current V8-focused flow

Do not silently override explicit user flags.

Output format

When you use this skill, report back in this structure:

Prompt: <final prompt sent>
Job ID: <job_id or "not returned">
Mode: <fast/relax/etc>
Visibility: <private/public>
Status: <submitted / polled / failed / dry-run>
Notes: <missing status endpoint, saved JSON path, or next step>

Simpler usage model

For day-to-day use, prefer this sequence:

1. python3 scripts/mj_doctor.py --fetch-user-state --transport browser
2. python3 scripts/run_imagine.py "<prompt>" --transport browser --sync-user-state
3. python3 scripts/run_imagine.py "<prompt>" --transport browser --sync-user-state --wait-page-assets --download

This reduces manual mistakes and keeps you in a low-frequency workflow. On this machine, browser transport is the preferred live path because raw HTTP requests are blocked by Cloudflare.

Success criteria for a usable generation

Treat a generation as verified only when all of these are true:

1. submit response contains a job_id
2. page resource entries contain 4 CDN image URLs for the same job_id
3. the image files are downloaded successfully to local disk

Normal Midjourney imagine behavior is a 4-image grid. Depending on the endpoint response, you may get one grid image file rather than four separately cropped files. This skill currently verifies and downloads the returned image assets as provided by Midjourney.

Extension path

After the user captures more browser requests, extend in this order:

1. Confirm job-status endpoint and final-image fields
2. Add result downloader
3. Add button-action support for upscale / variation
4. Add reference image upload flow
5. Add prompt-template helpers for common MJ styles

Confirmed non-status endpoints

• POST https://proxima.midjourney.com/ is currently treated as telemetry ingestion
• POST /api/v1/traces is currently treated as tracing/observability data
• GET /api/user-mutable-state is useful for reading current speed and visibility defaults

Do not mistake telemetry endpoints for job-status APIs.

GitHub-informed but experimental path

The skill includes an experimental recent-jobs reader based on public GitHub reverse-engineering notes. Treat it as best-effort support rather than a stable API contract.