본문으로 건너뛰기
cccskills
무료GitHub에 공개

generate-image

Generate illustrations, icons, game textures, sprites, and mockups from written descriptions using OpenAI or Google Gemini. The skill selects an available provider, saves the resulting image, and reports its location.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Generate images using AI. Use when asked to generate, create, or make images, textures, icons, sprites, artwork, visual assets, or mockups. Supports OpenAI (gpt-image-2) and Google Gemini (Nano Banana). Requires an API key for the chosen provider.

연동 도구OpenAIGemini
설치 방법 보기

이럴 때 유용합니다

  • Generate icons or illustrations from descriptions
  • Create game textures and sprites
  • Make mockups to explore visual ideas
  • Generate multiple visual assets in a batch

포함된 파일(1)

  • SKILL.md3.8 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Generate Image

You are an image generation assistant. When invoked, follow the workflow below.

Workflow

  1. Check for API keys — check whether SKILL_IMAGE_GEN_OPENAI_KEY and/or SKILL_IMAGE_GEN_GEMINI_KEY are set in the environment.
  2. If one key is set — use that provider. No need to ask.
  3. If both are set — pick based on context (OpenAI for polish, Gemini for speed), or ask if the user has a preference.
  4. If no keys are set — run the Onboarding section.
  5. Generate the image using the appropriate API reference.
  6. Tell the user where the image was saved.

Onboarding

Only run this if no keys are set. Guide the user conversationally.

  1. Ask which provider they'd like to use:
    • OpenAI (gpt-image-2) — High quality, excellent text rendering, paid per image
    • Google Gemini (Nano Banana) — Fast, free tier available, great for iteration
  2. Direct them to get an API key:
  3. Once they provide the key, set SKILL_IMAGE_GEN_OPENAI_KEY or SKILL_IMAGE_GEN_GEMINI_KEY in the current session and persist it to the appropriate shell profile.
  4. Proceed to generate the image they originally asked for.

API Reference: OpenAI

Method: POST URL: https://api.openai.com/v1/images/generations

Headers:

  • Authorization: Bearer <SKILL_IMAGE_GEN_OPENAI_KEY>
  • Content-Type: application/json

Body (JSON):

{
  "model": "gpt-image-2",
  "prompt": "<user prompt>",
  "n": 1,
  "size": "1024x1024",
  "quality": "medium"
}
FieldDefaultOptions
modelgpt-image-2gpt-image-2, gpt-image-1
size1024x10241024x1024, 1024x1536, 1536x1024, auto
qualitymediumlow, medium, high

Response: data[0].b64_json contains the base64-encoded image. Decode it and save to the output path. If data[0].url is present instead, download the image from that URL.

API Reference: Google Gemini (Nano Banana)

Method: POST URL: https://generativelanguage.googleapis.com/v1beta/models/<model>:generateContent

Headers:

  • x-goog-api-key: <SKILL_IMAGE_GEN_GEMINI_KEY>
  • Content-Type: application/json

Body (JSON):

{
  "contents": [{"parts": [{"text": "Generate an image: <user prompt>"}]}],
  "generationConfig": {"responseModalities": ["TEXT", "IMAGE"]}
}
FieldDefaultOptions
model (in URL)gemini-2.0-flash-expgemini-2.0-flash-exp, gemini-2.5-flash-image

Response: Find candidates[0].content.parts[] — look for a part with inlineData.data (base64 image) and inlineData.mimeType. Decode and save.

Error cases: error key (API error), promptFeedback.blockReason (safety block), finishReason: "SAFETY" (filtered).

Agent Guidelines

  • Choose the output path intelligently — save to the project's relevant directory (e.g., assets/, images/, or the current directory).
  • For game textures, enrich prompts with "seamless", "tileable", "game asset".
  • For batch generation, make multiple API calls in parallel.
  • If the user asks to switch providers or what options are available, explain both and help them set up.
  • Always create the output directory before saving.
  • Ensure special characters in the user's prompt are properly escaped in the JSON body.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Map an existing codebase into seven documents covering its technology, structure, architecture, conventions, integrations, tests, and concerns. Link findings to file evidence, mark unknowns, and highlight differences between stated plans and the actual implementation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Get oriented in an unfamiliar codebase
  • Prepare documentation for a project handover
  • Compare documented architecture with implementation
github/awesome-copilot4만2026년 10월 17일 업데이트

Assess a repository’s readiness for AI agents with AgentRC and generate a standalone HTML dashboard. Review scores across nine areas, see prioritized improvements, and optionally apply scoring policies tailored to an organization.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Assessing a repository’s readiness for AI agents
  • Prioritizing improvements from assessment results
  • Reviewing scores under an organization’s own policy
github/awesome-copilot4만2026년 10월 17일 업데이트

Generate coding agent instruction files from a project's actual code using AgentRC. Capture detected languages, frameworks, and conventions in one shared file or split rules by topic and project area, with a preview before writing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Create project instructions for VS Code Copilot
  • Refresh agent rules after project changes
  • Split monorepo instructions by project area
github/awesome-copilot4만2026년 10월 17일 업데이트

Customize AgentRC readiness assessments to match team or organization standards. Choose or create policies that adjust check importance, disable irrelevant checks, set pass thresholds, and define requirements for automated checks in CI workflows.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Set shared readiness standards across an organization
  • Focus assessments on AI tooling
  • Adjust the importance of individual checks
github/awesome-copilot4만2026년 10월 17일 업데이트

Analyze supplied ad performance data to identify wasted spend, strong campaigns, and next tests. Compare channels, assess whether test differences are meaningful, and produce budget reallocation recommendations with a prioritized action plan.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Identify ads and keywords to pause
  • Find campaigns and audiences worth scaling
  • Assess whether A/B test results are meaningful
github/awesome-copilot4만2026년 10월 17일 업데이트

Turn code files into learning resources by adding comments that explain syntax, programming concepts, and design choices. Adjust explanation depth and repetition to the reader’s knowledge while preserving file structure, encoding, and syntax.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

  • Add beginner-friendly explanations to existing code
  • Document the reasoning behind syntax and design choices
  • Adjust comment depth for readers with different experience
github/awesome-copilot4만2026년 10월 17일 업데이트

github의 스킬 모두 보기

이 스킬의 문제 신고