baoyu-skills/docs/codex-imagegen-backend.md

codex-imagegen Backend

Generate images via Codex CLI's built-in image_gen tool from non-Codex runtimes (e.g., Claude Code). The wrapper spawns codex exec --json and lets the user's existing Codex subscription drive image generation — no OPENAI_API_KEY required.

This backend implements the preferred_image_backend: codex-imagegen config key already referenced in several SKILL.md files across this repo.

Features

Feature	Status
Reliability: retry + exponential backoff	Default 2 retries
Verification: confirms image_gen was actually invoked (not bypassed)	Checks $CODEX_HOME/generated_images/{thread_id}/
Verification: PNG magic-byte sanity check	✓
Idempotency cache: reuses output for same prompt+aspect+refs	--cache-dir
Concurrency control: file lock prevents parallel codex exec collisions	Built-in
Structured logging: JSONL log file	--log-file
Token usage returned	Embedded in result JSON
--ref reference images	Repeatable
Unit tests	16 tests (parser / cache / validator)
Error classification: retryable vs non-retryable	9 error_kind values

Why this backend

Scenario	Conventional backend	This backend
You have a Codex subscription	OpenAI Images API costs add up per image	Subscription already covers it — zero marginal API cost
No OPENAI_API_KEY available	baoyu-image-gen needs an API key	codex login is enough
Want to use GPT Image 2	Only via OpenAI API	Codex's image_gen is GPT Image 2

Prerequisites

npm install -g @openai/codex
codex login            # signs in with your OpenAI account (subscription)
codex --version        # confirm >= 0.130

bun is preferred for running the wrapper. On macOS:

brew install oven-sh/bun/bun

If bun is missing, the shell entrypoint falls back to npx -y bun.

Usage

Direct CLI

# Inline prompt
./scripts/codex-imagegen.sh \
  --image /tmp/cat.png \
  --prompt "A friendly orange cat, watercolor"

# Prompt from file
./scripts/codex-imagegen.sh \
  --image cover.png \
  --prompt-file prompts/01-cover.md \
  --aspect 16:9

# Verbose mode for debugging
./scripts/codex-imagegen.sh -v --image dog.png --prompt "A corgi" --aspect 1:1

On success, stdout emits a single JSON line:

{"status":"ok","path":"/tmp/cat.png","bytes":2567101,"elapsed_seconds":53}

On failure, exit code is non-zero and stderr contains the error message.

Enabling within image skills

Image-generating skills (e.g., baoyu-cover-image, baoyu-article-illustrator) already support a preferred_image_backend preference. To route them through this backend, set the following in the corresponding EXTEND.md:

# ~/.baoyu-skills/baoyu-cover-image/EXTEND.md
preferred_image_backend: codex-imagegen

When the LLM runs the skill, it reads the preference and — guided by the ### codex-imagegen Backend section in CLAUDE.md — invokes scripts/codex-imagegen.sh.

Note

: The integration is mediated by the LLM reading CLAUDE.md. It is not a hard binding. If a skill does not route to the backend automatically, mentioning it explicitly in the prompt works.

Parameters

Flag	Required	Description
--image <path>	✓	Output PNG path (absolute recommended; relative paths are resolved against cwd)
--prompt <text>	one of	Prompt string (mutually exclusive with --prompt-file)
--prompt-file <path>	one of	Read prompt from file (mutually exclusive with --prompt)
--aspect <ratio>		Aspect ratio. Default 1:1. Common: 16:9, 9:16, 4:3, 2.35:1
--ref <file>		Reference image path (repeatable)
--timeout <ms>		codex exec timeout in ms. Default 300000
--retries <n>		Retry count on retryable errors. Default 2 (total attempts = retries + 1)
--retry-delay <ms>		Base delay between retries (exponential backoff). Default 1500
--cache-dir <path>		Enable idempotency cache (reuses output for same prompt+aspect+refs)
--log-file <path>		Structured JSONL log path (appended)
-v / --verbose		Mirror log entries to stderr
-h / --help		Show usage

Structured Output

On success, stdout contains a single JSON line:

{
  "status": "ok",
  "path": "/tmp/owl.png",
  "bytes": 1693831,
  "elapsed_seconds": 87,
  "thread_id": "019e40e8-daef-7c60-943d-5e7bb3f6cb3d",
  "attempts": 1,
  "cached": false,
  "usage": {
    "input": 110899,
    "cached_input": 83456,
    "output": 457,
    "reasoning": 47
  },
  "tool_calls": [
    {"tool": "shell", "status": "completed"},
    {"tool": "agent_message", "status": "completed"}
  ]
}

Cache hits return with elapsed_seconds: 0, cached: true, attempts: 0.

On failure, exit code is 1 and the JSON contains error and error_kind:

{
  "status": "error",
  "error": "image_gen was not invoked: no PNG in ...",
  "error_kind": "no_image_gen_tool_use"
}

Error Kinds

error_kind	Retryable	Meaning
codex_not_installed	✗	codex CLI not found
invalid_args	✗	Argument parsing error
prompt_file_missing	✗	--prompt-file path does not exist
spawn_failed	✓	codex exec exited non-zero
timeout	✓	Exceeded --timeout
no_image_gen_tool_use	✓	Agent did not invoke image_gen (it took another path)
output_missing	✓	Output file not created
invalid_png	✓	Output is not a valid PNG
agent_refused	✓	No thread_id in event stream (Codex refused to respond)
lock_busy	✗	Concurrency lock acquisition timed out

Measured Performance

Metric	Value
First-run latency	50–90 s
Cache-hit latency	< 0.3 s
Output dimensions	1024×1024, 1672×941 (16:9), etc. — chosen by image_gen
Output format	PNG (RGB, 8-bit)
Token usage per call	~110k input (~80k cached) + ~500 output
Quota source	Codex subscription (does not consume OpenAI API quota)
Default timeout	300 s (5 min)

Limitations & Risks

1. 5–10× slower than direct API. codex exec cold-starts the agent, loads the built-in image_gen SKILL.md, and runs reasoning before invoking the tool. Cache hits avoid this for repeated prompts.
2. ToS gray area. Codex's image_gen tool is designed for interactive use. Invoking it programmatically via codex exec from an external agent is not explicitly addressed by current OpenAI policies. Suggested guardrails:
   • Personal, low-volume use is reasonable.
   • Not recommended for production automation or high-volume batch jobs.
   • Users are responsible for ensuring their usage complies with applicable terms of service.
3. Sandbox permissions. The wrapper passes --sandbox danger-full-access so the spawned agent can move the rendered PNG out of $CODEX_HOME/generated_images/. This is necessary because the agent must cp/mv the file to the user-specified output path.
4. Concurrency = 1. The file lock serializes concurrent invocations to avoid codex exec collisions. Parallel calls queue.

Troubleshooting

Symptom	error_kind	Resolution
command not found: codex	codex_not_installed	npm install -g @openai/codex
codex exec fails	spawn_failed	Check codex login status; inspect raw_log path
Timeout	timeout	Pass --timeout 600000 (10 min) for slow networks
Agent skipped image_gen	no_image_gen_tool_use	Auto-retries; consider sharpening the prompt — abstract prompts let the agent wander
Output missing	output_missing	Agent did not cp to the target path; check raw_log for the actual save location under generated_images/
Lock held	lock_busy	Wait for the in-flight request to finish; or rm ~/.cache/baoyu-codex-imagegen/codex-exec.lock
Low image quality	—	Sharpen the prompt, try a different aspect, or supply --ref

Architecture

scripts/codex-imagegen.sh        # thin bash entrypoint
scripts/codex-imagegen/
├── main.ts        # parseArgs → cache → lock → retry loop → emit JSON
├── types.ts       # CliOptions, GenerateResult, GenError, ErrorKind
├── spawn.ts       # spawn codex exec --json --sandbox danger-full-access
├── parser.ts      # parse JSONL event stream → toolCalls, usage, thread_id
├── validator.ts   # verify image_gen invocation + PNG magic + file size
├── cache.ts       # cacheKey(sha256), FileLock, lookup/store
├── logger.ts      # JsonLogger (verbose stderr + JSONL file)
├── parser.test.ts
├── cache.test.ts
└── validator.test.ts

Run tests:

cd scripts/codex-imagegen && bun test

Internal Flow

flowchart LR
    CC[Claude Code / any caller]
    WRAPPER[scripts/codex-imagegen.sh]
    CODEX["codex exec --json<br/>--sandbox danger-full-access"]
    AGENT[Codex agent]
    TOOL[image_gen built-in tool]
    DEFAULT["$CODEX_HOME/<br/>generated_images/{thread_id}/"]
    OUT[/specified OUTPUT path/]

    CC -->|exec wrapper| WRAPPER
    WRAPPER -->|stdin: instruction| CODEX
    CODEX --> AGENT
    AGENT -->|tool call| TOOL
    TOOL -->|writes file| DEFAULT
    AGENT -->|agent cp/mv| OUT
    WRAPPER -->|verify + parse| CC

    classDef cc fill:#1e40af,color:#fff,stroke:#93c5fd
    classDef cdx fill:#7c2d12,color:#fff,stroke:#fdba74
    class CC,WRAPPER cc
    class CODEX,AGENT,TOOL cdx

Design Decisions

1. Bash entrypoint + TypeScript implementation — the shell wrapper picks the runtime (bun preferred, falling back to npx -y bun); TypeScript handles the orchestration, parsing, retry, cache, and logging. This mirrors the project's existing scripts/*.mjs and skills/<skill>/scripts/main.ts pattern.
2. --sandbox danger-full-access — necessary so the spawned agent can cp/mv the rendered PNG out of $CODEX_HOME/generated_images/ to the user-specified path. Standard sandboxes block this.
3. Parse the JSONL event stream — the final agent_message and intermediate command_execution events let the wrapper verify what actually happened (was image_gen called? did cp reach the right destination?), which is far more reliable than scraping freeform stdout.
4. Infrastructure, not a skill — this backend is a CLI utility that skills route to via preferred_image_backend. It belongs in scripts/, not skills/, because it has no SKILL.md and is never loaded directly by an agent.
5. File lock instead of internal queue — keeps the implementation small and works across multiple shell sessions or processes invoking the same wrapper concurrently.

Related Files

File	Role
scripts/codex-imagegen.sh	CLI entrypoint
scripts/codex-imagegen/	TypeScript implementation
docs/codex-imagegen-backend.md	This document
CLAUDE.md	Tells LLMs how to invoke this backend
.github/workflows/codex-imagegen-tests.yml	CI unit tests