Teamorouter Image

TeamoRouter Image

Use the scripts/teamorouter_image.py file resolved relative to this SKILL.md as the deterministic API client; do not assume the caller's working directory is the skill folder. It supports GPT Image 2 and GPT Image 2.5 Sunburst generation/editing, local size validation, dry runs, and secure local credential configuration without third-party Python packages.

User routing aliases

• Treat 本地 image2 as an explicit request to use this TeamoRouter API client with --model gpt-image-2.
• Treat 本地 image2.5 as an explicit request to use this TeamoRouter API client with --model gpt-image-2.5-sunburst.
• These phrases mean the locally configured API workflow, not an on-device image model or the previous local-machine generation route. Do not silently fall back to another provider or on-device model if the API fails.

Safety and authorization

• Never ask the user to paste an API key into chat, a prompt, a command argument, or a project file.
• If a key was exposed in chat, tell the user to revoke it and create a new one. Do not save or use the exposed key.
• Generation and editing are paid external actions. Prepare a dry run first unless the user already approved the exact call. Run a paid request only after clear authorization and include --confirm-spend.
• Do not retry a failed paid request automatically. Report the HTTP status and sanitized error, then ask before retrying if another charge is possible.
• A successful API response is not delivery. Confirm the output file exists and is non-empty before reporting completion.

Credential setup

Ask the user to run this themselves in a terminal so the key is entered through hidden input:

python3 scripts/teamorouter_image.py configure

The client first checks TEAMOROUTER_API_KEY, then its private per-user credentials file. configure creates that file with user-only permissions. Never inspect or print the stored secret.

Verify the stored credential without generating an image:

python3 scripts/teamorouter_image.py check-auth

Workflow

1. Validate the request locally and show the sanitized payload:

python3 scripts/teamorouter_image.py generate --prompt "..." --size 1024x1024 --quality high --dry-run

Select GPT Image 2 explicitly with --model gpt-image-2:

python3 scripts/teamorouter_image.py generate --model gpt-image-2 --prompt "..." --size 1024x1024 --quality high --dry-run

2. After explicit approval, submit with --confirm-spend and an explicit output directory:

python3 scripts/teamorouter_image.py generate --prompt "..." --size 1024x1024 --quality high --output-dir /absolute/output/path --confirm-spend

3. For edits, supply one or more existing images and optionally a same-size mask. Repeat --image for multiple references:

python3 scripts/teamorouter_image.py edit --image /absolute/input.png --prompt "..." --size 1024x1024 --input-fidelity high --output-dir /absolute/output/path --dry-run

python3 scripts/teamorouter_image.py edit --image /absolute/identity.png --image /absolute/style.png --prompt "Use the person from image 1 and the composition from image 2" --size 1024x1536 --output-dir /absolute/output/path --dry-run

4. Parse the JSON written to stdout. files contains the saved image paths. Verify each file before reporting success.

Use validate-size for a no-network check. Read references/api.md only when parameter or billing details are needed.

Defaults

• Default model is gpt-image-2.5-sunburst; use --model gpt-image-2 for the Image 2 route.
• size=1024x1024, quality=auto, n=1, output_format=png, background=auto, and generation moderation=auto.
• Explicit size is preferred because billing follows actual returned resolution. Use auto only when the user accepts variable output size and tier.
• Transparent generation requires PNG or WebP. The edit endpoint may still return no alpha channel even when transparent is requested.
• Streaming is intentionally omitted because the documented intermediate chunks currently contain no image.