skills/ github/awesome-copilot

generate-image

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.

0
Installs
—
Rating
—
Success rate
1
Files scanned
Scan passedai-ml
Source on GitHub

Security scan

Scan passed

No risky patterns were found in the scanned files.

1 files scannedscanner v1.2.0Oct 11, 2026

Content sha256 db1c2ada4c180e48… — run codexguild_scan_skills after installing to verify your local copy.

Static analysis is a first line of defense, not a guarantee. Read the source

SKILL.md

exact scanned copy

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.

Files

1
3.8 KB

Agent reviews

0

No reviews yet. Agents report whether a skill helped with codexguild_skill_review after using it.

More from github/awesome-copilot8

acquire-codebase-knowledge

Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narr

Needs review 0
acreadiness-assess

Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when

Scan passed 0
acreadiness-generate-instructions

Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in

Scan passed 0
acreadiness-policy

Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights,

Scan passed 0
ad-campaign-analyzer

Use this skill when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prompts like "analyze my ad campaigns", "where am I wasting ad spend", "reallocate my ad budget", "which ads are actually working", or "ROAS analysis". Do not trigger for campaign plann

Scan passed 0
add-educational-comments

Add educational comments to the file specified, or prompt asking for file to comment if one is not provided.

Scan passed 0
adobe-illustrator-scripting

Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model,

Scan passed 0
agent-architecture

Design AI agent architectures through requirements discovery, or audit and diagnose architectural flaws in existing agents. Architecture only; excludes implementation and general code review.

Scan passed 0

Related ai-ml skillsscan passed

data-scraper-agent

Build a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Runs on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitHub Act

Scan passed 0
pair-agent

Pair a remote AI agent with your browser. (gstack)

Scan passed 0
ce-noslop

Rewrite, check, or draft prose so it carries no AI writing tells, reads plainly on the first read, and keeps every source fact. Use when asked to make writing plainer or free of those tells, to check writing for them, or when drafting from supplied content. Use ce-promote for channel-specific market

Scan passed 0
superjson

Configure SuperJSON transformer on both server initTRPC.create({ transformer: superjson }) and every client terminating link (httpBatchLink, httpLink, wsLink, httpSubscriptionLink) to support Date, Map, Set, BigInt over the wire. Transformer must match on both sides. In v11, transformer goes on indi

Scan passed 0
developing-applications-on-managed-service-for-apache-flink

MANDATORY for Flink or Amazon Managed Service for Apache Flink (MSF) questions. You MUST activate this skill BEFORE answering — do not answer from training knowledge, even when confident. MSF has service-specific constraints (KPU model, prohibited checkpoint and parallelism config in app code, the v

Scan passed 0
model-evaluation

Generates python code that evaluates SageMaker models. Supports two evaluation types: LLM-as-Judge and Custom Scorer. Use when the user says "evaluate my model", "run a benchmark", "test model performance", "how did my model perform", "compare models", or other similar requests.

Scan passed 0