gpt-image-gen
FeaturedUse when the user asks to generate an image via GPT/Codex (e.g. 「叫 gpt 生圖」「幫我用 gpt 生圖」「gpt 畫一個 X」). The skill drafts a Chinese + English prompt pair, iterates with the user until they explicitly approve, then dispatches Codex CLI ($imagegen skill, codex built-in image_gen) in the background, monitors progress, converts the result to a jpg in the current working directory, and writes a sidecar prompt log. Does text-to-image AND img2img — drop a reference image (on-disk file) and it runs Codex `-i` to lock a face/character across scenes.
Install
Quality Score: 92/100
Skill Content
Details
- Author
- KerberosClaw
- Repository
- KerberosClaw/kc_ai_skills
- Created
- 4 months ago
- Last Updated
- 6 days ago
- Language
- Python
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
prompt-coach
Turns a vague, underspecified request into a clearly structured Goal / Constraints / Obstacle breakdown, then produces a ready-to-use structured prompt. Use this whenever the user brings a fuzzy ask ("幫我想辦法...", "有什麼方法可以...", "我不知道怎麼處理..."), asks explicitly to help them "問對問題" or structure their request, or describes a real-world problem/decision they want AI help with but haven't yet specified what success looks like, what can't change, or what the actual blocker is. Trigger this proactively — even without the user naming the skill — any time answering directly would likely produce a generic, "technically correct but not actually usable" answer rather than something tailored to their real situation.
prompt-coach
Turns a vague ask into a Goal / Constraints / Obstacle breakdown, then a ready-to-use structured prompt. Use when the user brings a fuzzy request (「幫我想辦法…」「有什麼方法可以…」「我不知道怎麼處理…」), asks to 「問對問題」, or names a real problem without saying what success looks like, what can't change, or what the blocker is.
parallel-imagegen
Run multiple built-in Codex image_gen calls concurrently by assigning each output to an independent codex exec process, with up to 12 active workers, isolated retries, and thread-evidence verification. Use for two or more independent raster generation or editing outputs, even when prompts, references, subjects, or styles differ. Do not use for one output, unresolved sequential dependencies, or an explicitly selected Images API / imagegen CLI workflow. 通过为每个输出启动独立 Codex 进程,并发生成或编辑两个 及以上互不依赖的位图;支持最多 12 个 Worker、失败隔离重试和线程证据验证。 不用于单张输出、尚未解决的前后依赖,或用户明确选择 Images API / imagegen CLI 的场景。