OpenAI-Compatible Images Skill

This is the Standalone distribution. Read configuration only from auth.json beside this installed skill; do not discover, merge, or fall back to the Codex Plugin configuration under ~/.codex/openai-compatible-imagegen/. When the Codex Plugin distribution is active, follow its bundled skills/openai-compatible-imagegen/SKILL.md instead of this CLI workflow. Standalone uses the configured API Key provider: openai-compatible, atlas, xai-images, gemini-interactions, or gemini-generate-content, as explicitly configured. ChatGPT subscription handoff is a Plugin-only capability. Atlas supports text-to-image generation with PNG or JPEG output; edits and native transparency are unsupported. Never switch protocols to work around a failure.

Use the bundled script for API calls. Resolve $SkillDir from the physical directory containing this SKILL.md; never substitute another same-named installation. Run $SkillDir/scripts/imagegen.py info before an API request and require both script_path and auth_json to remain under $SkillDir. Stop and report the path mismatch instead of using a different copy. When validating this skill through another agent, require it to report the absolute imagegen.py path actually executed.

Do not rewrite the API client inline. The script is the authority for request validity: do not reject, rewrite, or ask the user to change a model, size, or transparency request based on remembered provider limitations. Run the command and report its actual result. Only a validation error emitted by the script or an API response can establish that the request failed.

Workflow

For a v2 provider/model configuration, run list-models before selecting an API model. Resolve the user's choice by exact profile ID, unique alias, or unique actual model ID; clarify multiple matching channels. Use --profile explicitly and preserve per-call native JSON through --parameters; JSONL rows use modelProfileId and parameters. Do not change active_profile for a one-call preference. Use the configured protocol (openai-compatible, atlas, xai-images, gemini-interactions, or gemini-generate-content), never infer or switch it from a model name. See model configuration for v2 defaults and parameter fields. ChatGPT handoff remains Plugin-only.

1. Run info to inspect the local configuration. If auth.json is missing, run scripts/quick-init.py.
2. Choose one mode:
   • generate: text-to-image.
   • edit: image editing, inpainting, or reference-image work.
   • batch: JSONL generation with limited concurrency.
   • apply-transparency: run one declared local transparency route on an existing PNG.
   • info: redacted configuration summary.
3. Before constructing the command, interpret the request and decide the purpose, subject, composition, visual style, target size, aspect ratio, quality, format, background, transparency, reference files, and output location. Preserve explicit per-row and shared values; use agent judgment only for omitted intent, and leave a parameter unset when auth.json should decide it.
4. After command construction, runtime parameter priority is per-row batch fields > shared command flags > auth.json defaults > built-in defaults. An agent-inferred value emitted as a shared flag follows this runtime rule and overrides auth.json.
5. Call scripts/imagegen.py and report the output paths and any manifest.

Do not replace an execution with a handwritten error record. In particular, gpt-image-2 requests at 2K or 4K with --transparent must reach the script unchanged. Do not claim they require 1K, gpt-image-1.5, or an opaque background, and do not offer those changes before the script or API returns an error. --transparent is delivery intent; only the resolved native-alpha route sends the API transparency parameter.

Publish every complete, decodable API image. Requested count, pixel size, or format deviations are factual warnings, never reasons to hide a valid original. ok=true means at least one API original was published; delivery_ready independently reports whether requested transparency, transforms, and QA passed. Treat delivery_size as a separate local transform and report both source and derived paths when it is used.

When the user describes an image, form a concise, structured prompt. Include the intended use, subject and relationships, composition, style or medium, audience or context, delivery constraints, text requirements, and concrete exclusions. For a batch, state which properties stay consistent and which properties vary. Do not add domain-specific assumptions that the user did not provide.

Treat game art as one peer industry use case alongside product, editorial, marketing, interface, diagram, and photographic work. Preserve game-specific details when the user supplies them, but do not make them the default for unrelated requests.

Never read, print, quote, or summarize secret values in auth.json.

The script accepts Base64 and URL image responses and validates them before publication. Do not add response_format for GPT Image models. Preserve valid peers when another item is invalid or exceeds resource limits. Use the parameter reference for count, format, and validation limits; do not infer semantic quality from these checks. Returned image URLs are downloaded without API credentials.

If a returned image URL fails with a TLS EOF while direct download is disabled, explain the two explicit authorization choices: --allow-direct-url-download for one command or auth.json url_download.proxy_mode="direct" persistently. Do not enable either choice without user approval.

When auth.json proxy.url is configured, generation, edit, and returned image URL requests use that HTTP proxy. Do not expose the URL or change it automatically. A proxy failure stops the operation; never retry through the environment proxy or a direct connection. url_download.proxy_mode="direct" overrides the proxy only for returned image downloads.

Local Auth

auth.json is local-only and must not be committed.

Requires Python 3.12 or newer. Set SkillDir to the physical installed directory before using the examples. Windows uses python; macOS/Linux use python3.

Initialize it after installation:

Windows PowerShell:

$SkillDir = "C:/path/to/openai-compatible-imagegen"
python "$SkillDir/scripts/quick-init.py"

macOS or Linux shell:

SkillDir="/absolute/path/to/openai-compatible-imagegen"
python3 "$SkillDir/scripts/quick-init.py"

For scripted setup with environment-variable authentication:

Windows PowerShell:

$SkillDir = "C:/path/to/openai-compatible-imagegen"
python "$SkillDir/scripts/quick-init.py" `
  --non-interactive `
  --base-url "https://example.com/v1" `
  --model "gpt-image-2" `
  --auth-method env `
  --api-key-env "OPENAI_API_KEY" `
  --postprocess

macOS or Linux shell:

SkillDir="/absolute/path/to/openai-compatible-imagegen"
python3 "$SkillDir/scripts/quick-init.py" \
  --non-interactive \
  --base-url "https://example.com/v1" \
  --model "gpt-image-2" \
  --auth-method env \
  --api-key-env "OPENAI_API_KEY" \
  --postprocess

The imagegen.py init command remains available for copying the template.

API key options:

• Put the key directly in auth.json as api_key.
• Put an environment variable name in api_key_env, then set that variable.

If both are present, the script uses api_key unless it is a template placeholder.

Important configuration fields:

• protocol: openai-compatible (default), atlas, xai-images, gemini-interactions, or gemini-generate-content. For provider/model structures, set it in the provider; see model configuration.
• base_url: provider base URL; OpenAI-compatible services usually use /v1, while Atlas uses its service root.
• api_key or api_key_env: local authentication.
• model: default image model.
• proxy.url: optional complete http:// or https:// proxy URL for this provider. Credentials, paths, queries, fragments, and SOCKS URLs are not accepted.
• url_download.proxy_mode: environment or explicitly authorized direct.
• defaults: values used when a request omits a parameter.
• postprocess.enabled: default permission for local transparency processing, including native fallback.
• transparency.default_route: native-alpha, chroma-matting, emissive-alpha, or mask-alpha.
• transparency.native: native transparency permission, optional model capability declaration, parameter retry policy, and local fallback route.
• transparency.prompt_only_allow: exact model/mode/size combinations verified for prompt-only alpha generation, primarily used when local processing is not preferred.
• transparency.llm_assisted: bounded agent-guided route selection and parameter tuning after an unmet result.

The old capabilities.transparent_background setting is removed. If it remains in auth.json, report the migration error and ask for that field to be removed. Native transparency uses the current transparency.native policy.

Transparency Workflow

Treat --transparent as delivery intent. The CLI --background accepts only auto or opaque. When the resolved route is native-alpha, the runtime sends API background=transparent, PNG output, and a real-alpha prompt contract; local routes omit that parameter.

Map an explicit user preference to an explicit per-run switch: use --postprocess when the user allows or requests local processing. --no-postprocess disables local transparency pixel changes, including native fallback. For non-native routes, an exact prompt-only rule selects prompt-alpha; otherwise the runtime keeps the prompt unchanged and inspects returned alpha. The switch does not disable a selected native request. Explicit delivery transforms may still run after transparency passes. Omitting both switches inherits postprocess.enabled.

The native request and background controls below apply to OpenAI-compatible. Atlas, xAI, and Gemini have no dedicated native-alpha transport here; use compatible local delivery on saved PNG originals. For v2 API calls, resolve transparency from the selected profile, not the top-level host/local policy.

Choose the request route before sending the request:

1. Honor an explicit --transparency-route or batch transparency_route; an explicit local route conflicts with --no-postprocess.
2. Select a configured native-alpha default regardless of the local processing switch; it requires transparency.native.enabled=true. Otherwise use transparency.default_route when local post-processing is allowed.
3. When local processing is disabled, use prompt-alpha only if transparency.prompt_only_allow exactly matches the model, mode, and pixel size.
4. For every other size, including 2K and 4K, continue the API request with the user's requested model, size, and prompt unchanged, preserve every returned original, and inspect source alpha without local pixel changes. Never turn model/size folklore into a local refusal.
5. Report incomplete or contradictory contracts, such as disabled native transparency, mask-alpha without a mask, or a local route combined with --no-postprocess. An explicit prompt-alpha without an exact allow rule becomes source-alpha inspection: keep the prompt unchanged, call the API, and report the returned original. Do not silently change the model, endpoint, size, or retry policy.

Ordinary API requests omit background by default. Pass auto or opaque only when the user explicitly requests that API option. If an explicit background option is rejected, explain the failure and ask before submitting a new request without it; do not infer parameter rejection from a timeout or an ambiguous error. The configured, limited retry for native transparency remains unchanged.

Native transparency has a separate configured retry: a transparency-related HTTP 400/422 allows one same-request retry without the background parameter when transparency.native.retry_without_parameter=true. The model, provider, endpoint, prompt, size, and editing inputs remain the same. Set the switch to false to stop on rejection. A successful retry uses transparency.native.fallback_route only when local processing is allowed; otherwise it inspects the returned alpha without local pixel changes. A successful native request that returns an opaque image is preserved with unmet transparency in Standalone; the Plugin additionally selects its local fallback for that case when processing is allowed. See the parameter reference for policy fields.

Retry permission and local processing permission are independent. Keep the user's processing choice throughout retries. Preserve originals, include validated derivatives when local processing succeeds, and report the final route, API attempts, and delivery status.

Choose among all declared deterministic routes rather than treating chroma keying as the universal method. Use chroma-matting for isolated subjects rendered against a known solid key color. Its default edge-connected color range protects matching subject colors; select background_scope=global only when the declared key background must also be removed from enclosed holes such as rings, handles, counters, and lettering. Use emissive-alpha for particles, fire, lightning, smoke, and glow rendered against pure black; it converts luminance to continuous alpha and preserves disconnected falloff. Use mask-alpha when an explicit alpha, luminance, red, green, or blue mask channel exists, including masks prepared with traditional channel-selection or layer-mask workflows. A mask path and any black/white source matte color are input facts, not values the deterministic processor guesses. Hair, fur, glass, translucent fabric, reflected light, and mixed smoke/background imagery without a trusted mask or controlled plate are outside reliable deterministic extraction; preserve the original and report unmet instead of guessing.

Build the base prompt from the user's subject, composition, style, and semantic color requirements only. Treat transparency as a delivery flag, not prompt text. Do not manually add a transparent-background instruction, real-alpha contract, alpha 0, checkerboard background, key-color background, pure-black emissive contract, or mask contract before invoking the command. resolve_plan selects and appends the verified route contract exactly once. When an explicit prompt-alpha has no exact allow rule, the resolved inspect-alpha plan must send the semantic base prompt unchanged. Preserve colors the user explicitly requires on the subject; do not reinterpret them as a background instruction.

Keep transparency.prompt_only_allow empty unless the configured backend has been verified for that exact model, mode, and pixel size. A 1K rule is an exact pixel-size rule such as 1024x1024; do not downgrade a 2K or 4K request to make it match. Size alone does not block generation; follow the route-selection order above.

The prompt-only route is a request to the model, not a guarantee. After an API response is written:

• If native alpha or local processing passes, report transparency.status=pass and delivery_ready=true.
• If it does not pass, keep ok=true, set delivery_ready=false, return the API image unchanged, and add a warning explaining the unmet transparency condition.
• If a delivery resize or grid transform depends on transparency and transparency is unmet, skip that transform for that image and return the API image unchanged.

For multiple items in a completed API response, evaluate and publish each original independently. A malformed item, target collision, transform failure, or failed transparency check must not discard valid peers. Atlas multi-candidate requests collect one response per candidate before publication; if any candidate request fails, the group is not published. Do not split or repeat an unsuccessful group automatically.

LLM-assisted adjustment

Read the effective policy from info.

When llm_assisted.enabled=true and the first result is unmet:

1. Inspect the original API image, route checks, warnings, and previews. Count the first local processing run as attempt 1.
2. Re-run the original image with apply-transparency only while the total attempt count remains within max_attempts.
3. Tune only documented route parameters when allow_parameter_tuning=true. Treat them as processing controls, not QA controls: every attempt must pass the unchanged deterministic quality gate and multi-background preview review. Never lower a tolerance merely to make a failed result report pass.
4. Change routes only when allow_route_change=true and the candidate route's input contract is satisfied. Never invent a mask.
5. Send another image API request only when allow_api_retry=true; keep the configured model, endpoint, and requested size.
6. Never generate or execute image-processing code, install a runtime, download weights, or start a local model.

If every permitted attempt remains unmet, return the original API image and its factual warnings. The skill informs the user; it does not hard-block or hide the image.

Each local route records an 8-bit alpha_pipeline: background or mask profiling, matte method, refinement, optional Remove Matte/Defringe cleanup, and the black/white/gray/checker preview contract. Do not apply hard component cleanup to emissive effects; disconnected particles and soft falloff are intentional. For explicit masks, use threshold, expand, feather, gamma, and min_component_area only when the requested matte needs those operations. Use matte=black|white only when that source matte color is known; this cleanup changes partial-alpha edge colors and preserves pixels that the trusted mask marks fully opaque.

An HTTP error happens before an image exists and is separate from transparency QA. A 4xx response is recorded as error_kind=api_rejected with its status_code; it is not reported as transparency.status=unmet. For edit requests, technical reference metadata may be attached with status=not_evaluated; reference semantics are not automatically judged or used to block the API request.

Commands

All commands can run from any working directory.

Configuration summary:

Windows PowerShell:

python "$SkillDir/scripts/imagegen.py" info

macOS or Linux shell:

python3 "$SkillDir/scripts/imagegen.py" info

Text-to-image:

Windows PowerShell:

python "$SkillDir/scripts/imagegen.py" generate `
  -p "Editorial still life of a ceramic tea set on a light wood table, soft window light, space for a headline on the left, no text" `
  -f "outputs/tea-set.png" `
  --aspect 4:3 `
  --resolution 1K `
  --quality high

macOS or Linux shell:

python3 "$SkillDir/scripts/imagegen.py" generate \
  -p "Editorial still life of a ceramic tea set on a light wood table, soft window light, space for a headline on the left, no text" \
  -f "outputs/tea-set.png" \
  --aspect 4:3 \
  --resolution 1K \
  --quality high

Reference-image edit:

Windows PowerShell:

python "$SkillDir/scripts/imagegen.py" edit `
  -p "Keep the subject and camera angle, replace the background with a neutral studio wall, preserve realistic shadows" `
  -i "input.png" `
  -f "outputs/studio-edit.png"

macOS or Linux shell:

python3 "$SkillDir/scripts/imagegen.py" edit \
  -p "Keep the subject and camera angle, replace the background with a neutral studio wall, preserve realistic shadows" \
  -i "input.png" \
  -f "outputs/studio-edit.png"

Batch generation:

Windows PowerShell:

python "$SkillDir/scripts/imagegen.py" batch `
  --input "prompts.jsonl" `
  --out "outputs/imagegen" `
  --concurrency 3

macOS or Linux shell:

python3 "$SkillDir/scripts/imagegen.py" batch \
  --input "prompts.jsonl" \
  --out "outputs/imagegen" \
  --concurrency 3

Transparent single-subject output:

Windows PowerShell:

python "$SkillDir/scripts/imagegen.py" generate `
  -p "A clean isolated ceramic vase, front three-quarter view, no lettering" `
  -f "outputs/vase.png" `
  --asset `
  --transparent

macOS or Linux shell:

python3 "$SkillDir/scripts/imagegen.py" generate \
  -p "A clean isolated ceramic vase, front three-quarter view, no lettering" \
  -f "outputs/vase.png" \
  --asset \
  --transparent

Apply a declared local route to an existing image:

Windows PowerShell:

python "$SkillDir/scripts/imagegen.py" apply-transparency "source.png" `
  --out "outputs/source-transparent.png" `
  --route emissive-alpha `
  --transparency-param "black_point=8" `
  --transparency-param "gamma=1.2"

macOS or Linux shell:

python3 "$SkillDir/scripts/imagegen.py" apply-transparency "source.png" \
  --out "outputs/source-transparent.png" \
  --route emissive-alpha \
  --transparency-param "black_point=8" \
  --transparency-param "gamma=1.2"

The command exits after writing its JSON result. status=unmet returns the source image path, does not create an --out duplicate, and still exits successfully; use delivery_ready to distinguish a valid transparent delivery from a preserved original.

Inspect and validate a delivered file:

Windows PowerShell:

python "$SkillDir/scripts/imagegen.py" inspect-image "outputs/tea-set.png" `
  --components `
  --expected-size 1536x1152

macOS or Linux shell:

python3 "$SkillDir/scripts/imagegen.py" inspect-image "outputs/tea-set.png" \
  --components \
  --expected-size 1536x1152

Create delivery-size previews:

Windows PowerShell:

python "$SkillDir/scripts/imagegen.py" preview-board "outputs/vase.png" `
  --size 64x64 `
  --size 256x256 `
  --preview-background transparent `
  --preview-background white `
  --out-dir "outputs/vase-previews"

macOS or Linux shell:

python3 "$SkillDir/scripts/imagegen.py" preview-board "outputs/vase.png" \
  --size 64x64 \
  --size 256x256 \
  --preview-background transparent \
  --preview-background white \
  --out-dir "outputs/vase-previews"

Parameters

Core parameters:

• -p, --prompt: required for generate and edit.
• -f, --file: output file.
• -i, --image: reference image; repeat for multiple files.
• -m, --mask: edit mask.
• --size: exact pixel size.
• --aspect: 1:1, 16:9, 4:3, 3:4, or 9:16.
• --resolution: 1K, 2K, or 4K when using --aspect.
• --quality: auto, low, medium, high, xhigh, or max. The last two require model/provider support; Atlas retains low, medium, and high. Never downgrade quality automatically.
• --n: number of images returned by one request, from 1 to 16.
• --format: png, jpeg, or webp.
• --background: auto or opaque; transparent was removed.
• --transparent: transparent delivery intent; forces PNG and lets the resolved route decide whether to send the native API parameter.
• --asset: explicit single visual-deliverable intent; prefers PNG and does not imply a particular industry.
• --concurrency: limited batch concurrency.
• --allow-direct-url-download: explicit one-command authorization for direct returned-URL downloads.

Post-processing parameters: