Agent skill

Image Generation

Generate, edit, and iterate raster images from text prompts or reference images with GPT Image, Nano Banana, or Seedream.

Apache-2.0Auto-check: notesMedia & Creative

Install Image Generation

skills CLI

$ npx skills add Negai-ai/AgentClaw --skill image-generation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install Negai-ai/AgentClaw image-generation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/Negai-ai/AgentClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agentclaw/skills/builtin_skills/image-generation .claude/skills/image-generation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "image-generation" agent skill from https://github.com/Negai-ai/AgentClaw/tree/main/agentclaw/skills/builtin_skills/image-generation into .claude/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/Negai-ai/AgentClaw/tree/main/agentclaw/skills/builtin_skills/image-generation

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add Negai-ai/AgentClaw --skill image-generation -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install Negai-ai/AgentClaw image-generation --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Negai-ai/AgentClaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/agentclaw/skills/builtin_skills/image-generation .agents/skills/image-generation && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "image-generation" agent skill from https://github.com/Negai-ai/AgentClaw/tree/main/agentclaw/skills/builtin_skills/image-generation into .agents/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add Negai-ai/AgentClaw --skill image-generation -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install Negai-ai/AgentClaw image-generation --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Negai-ai/AgentClaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/agentclaw/skills/builtin_skills/image-generation .cursor/skills/image-generation && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "image-generation" agent skill from https://github.com/Negai-ai/AgentClaw/tree/main/agentclaw/skills/builtin_skills/image-generation into .cursor/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/Negai-ai/AgentClaw.git --path agentclaw/skills/builtin_skills/image-generation

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add Negai-ai/AgentClaw --skill image-generation -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install Negai-ai/AgentClaw image-generation --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Negai-ai/AgentClaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/agentclaw/skills/builtin_skills/image-generation .gemini/skills/image-generation && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "image-generation" agent skill from https://github.com/Negai-ai/AgentClaw/tree/main/agentclaw/skills/builtin_skills/image-generation into .gemini/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install Negai-ai/AgentClaw image-generation

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add Negai-ai/AgentClaw --skill image-generation -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/Negai-ai/AgentClaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/agentclaw/skills/builtin_skills/image-generation .github/skills/image-generation && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "image-generation" agent skill from https://github.com/Negai-ai/AgentClaw/tree/main/agentclaw/skills/builtin_skills/image-generation into .github/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add Negai-ai/AgentClaw --skill image-generation -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install Negai-ai/AgentClaw image-generation --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/Negai-ai/AgentClaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/agentclaw/skills/builtin_skills/image-generation .opencode/skills/image-generation && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "image-generation" agent skill from https://github.com/Negai-ai/AgentClaw/tree/main/agentclaw/skills/builtin_skills/image-generation into .opencode/skills/image-generation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "image-generation", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: image-generation
GitHub stars: 330
Token cost: ~1.9k tokens
SKILL.md length: 588 words
Files: 8 (incl. scripts, references)
Skills in repo: 1
Repo updated: Jun 8, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Generate, edit, and iterate raster images from text prompts or reference images with GPT Image, Nano Banana, or Seedream.

Works in 7 steps: Capture the visual brief: subject,… → Pick the provider. OpenAI is the… → Check the provider API key before… → …
Visual asset creation
SKILL.md covers Provider Selection, Workflow, API Key Handling and OpenAI Quick Start, plus 3 more sections
Runs Python scripts from its folder; calls python; reaches api.squarefaceicon.org; needs OPENAI_IMAGE_KEY and GOOGLE_IMAGE_KEY

What it does

Image Generation is an agent skill from Negai-ai/AgentClaw. Generate, edit, and iterate raster images from text prompts or reference images with GPT Image, Nano Banana, or Seedream. Use for visual asset creation, concept art, product/mockup imagery, style exploration, thumbnails, illustrations, and image transformation workflows across image provider APIs.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts and reference files (for example `references/nano_banana.md`, `references/openai.md` and `references/provider_contract.md`).

It sits in Media & Creative, covering Image generation. It works with Google Gemini and OpenAI. The repository describes itself as: AgentClaw turns one-sentence ideas into reusable Claw capabilities. Build less boilerplate with declarative workflows, computer browser code file control, MCP, Skills, memory… The licence is Apache-2.0.

When your agent uses it

Visual asset creation
Product/mockup imagery
Style exploration
Image transformation workflows across image provider APIs

Example prompts

“/image-generation”

Requirements

Python 3
A credential in OPENAI_IMAGE_KEY
A credential in GOOGLE_IMAGE_KEY

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

Capture the visual brief: subject, style, composition, aspect ratio, output count, quality, format, destination folder, and any reference…
Pick the provider. OpenAI is the supported default in this skill.
Check the provider API key before calling the script. If the key is missing, tell the user the exact variable to configure; after the user…
Read the matching provider reference when API parameters, edits, masks, streaming, or model limits matter.
Use the provider script for deterministic file output when possible; otherwise write a small one-off call using the same output contract.
Save generated files to the requested path, or to generated_images when no path is specified.
Return the saved file paths, output_dir, provider/model, size/quality/format, revised prompt when available, and any provider response ID…

What it can do on your machine

Read from SKILL.md and the folder at commit 034efd1. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 3 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- python
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
- api.squarefaceicon.org
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
- OPENAI_IMAGE_KEY
- GOOGLE_IMAGE_KEY
- ARK_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Image Generation loads about 1.9k tokens when it runs, and up to ~7k if it reads all its reference files. Until then it costs about 79 tokens; SKILL.md has 588 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~79
When it runs · the whole SKILL.md, loaded when a task matches: ~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

NoteMentions a .env fileSKILL.md:26

the key, write/update it in the project `.env` and update the current temporary environment before retrying.

NoteMentions a .env fileSKILL.md:40

The bundled runners automatically load `.env` before reading these variables. They check `AGENTCLAW_PROJECT_DIR/.env`, t

NoteMentions a .env fileSKILL.md:42

provides the value, update the project `.env` and the current temporary environment for this session before rerunning t

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from Negai-ai/AgentClaw at commit 034efd1, republished under its Apache-2.0 licence (© Negai-ai). 588 words, ~1,878 tokens.

Download SKILL.mdSave it as .claude/skills/image-generation/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.

name: image-generation
description: Generate, edit, and iterate raster images from text prompts or reference images with GPT Image, Nano Banana, or Seedream. Use for visual asset creation, concept art, product/mockup imagery, style exploration, thumbnails, illustrations, and image transformation workflows across image provider APIs.

Image Generation Skill

Use this skill for image creation and image editing work that should call an image provider API and save usable raster files.

Provider Selection

Current complete provider:

OpenAI GPT Image Image API: read references/openai.md; use scripts/openai_generate_image.py for repeatable command-line generation and editing. This runner also accepts an OpenAI-compatible base_url for GPT Image compatible providers.
Nano Banana image generation: read references/nano_banana.md; use scripts/nano_banana_generate_image.py for Nano Banana 2, Nano Banana Pro, and Nano Banana generation/editing.
Seedream image generation on Volcengine Ark: read references/seedream.md; use scripts/seedream_generate_image.py for Seedream 5 text-to-image, image-to-image, coherent image groups, streaming, and web search.

Reserved provider integration:

Future providers should add one references/<provider>.md file and one scripts/<provider>_generate_image.py runner following references/provider_contract.md.

Workflow

Capture the visual brief: subject, style, composition, aspect ratio, output count, quality, format, destination folder, and any reference images.
Pick the provider. OpenAI is the supported default in this skill.
Check the provider API key before calling the script. If the key is missing, tell the user the exact variable to configure; after the user provides or confirms the key, write/update it in the project .env and update the current temporary environment before retrying.
Read the matching provider reference when API parameters, edits, masks, streaming, or model limits matter.
Use the provider script for deterministic file output when possible; otherwise write a small one-off call using the same output contract.
Save generated files to the requested path, or to generated_images when no path is specified.
Return the saved file paths, output_dir, provider/model, size/quality/format, revised prompt when available, and any provider response ID. For user-visible Markdown images, use browser-safe URLs only; if the script returns local output_paths, call create_download_url for each image and use the returned URL instead of embedding local paths.

Show full SKILL.md (295 more words)Show less

API Key Handling

Required keys by provider:

OpenAI official or compatible GPT Image: OPENAI_IMAGE_KEY. Compatible services may also need the optional endpoint override OPENAI_BASE_URL or --base-url.
Nano Banana: GOOGLE_IMAGE_KEY.
Seedream on Volcengine Ark: ARK_API_KEY.

The bundled runners automatically load .env before reading these variables. They check AGENTCLAW_PROJECT_DIR/.env, the current working directory .env, and the AgentClaw project .env, then copy loaded values into the script process environment without overriding already exported variables.

When a selected provider key is not configured, tell the user which key is needed and wait for the user to provide or configure it. After the user provides the value, update the project .env and the current temporary environment for this session before rerunning the provider script. Keep secrets out of prompts, logs, references, tests, and generated reports.

All bundled runners default to generated_images and include output_dir plus absolute_output_dir in their JSON result. These are local filesystem directories, not browser URLs.

OpenAI Quick Start

bash

python agentclaw/skills/builtin_skills/image-generation/scripts/openai_generate_image.py \
  --prompt "A clean product hero image of a compact desktop AI assistant device" \
  --output-dir generated_images \
  --model gpt-image-2

For explicit GPT Image output parameters:

bash

python agentclaw/skills/builtin_skills/image-generation/scripts/openai_generate_image.py \
  --prompt "A polished app icon for AgentClaw, sharp claw mark plus workflow nodes" \
  --model gpt-image-2 \
  --size 1024x1024 \
  --quality high \
  --format png

For an OpenAI-compatible image service:

bash

python agentclaw/skills/builtin_skills/image-generation/scripts/openai_generate_image.py \
  --prompt "A square face icon in a clean 3D style" \
  --base-url https://api.squarefaceicon.org/v1 \
  --model gpt-image-2 \
  --size 1024x1024

For an edit or reference-image composition:

bash

python agentclaw/skills/builtin_skills/image-generation/scripts/openai_generate_image.py \
  --prompt "Create a cohesive product bundle image using these reference items" \
  --input-image body-lotion.png \
  --input-image soap.png \
  --output-dir generated_images

For a masked edit:

bash

python agentclaw/skills/builtin_skills/image-generation/scripts/openai_generate_image.py \
  --prompt "Replace the selected area with a small indoor pool" \
  --input-image room.png \
  --mask-image mask.png

Nano Banana Quick Start

bash

python agentclaw/skills/builtin_skills/image-generation/scripts/nano_banana_generate_image.py \
  --prompt "A professional product photo of an AI automation workspace on a clean desk" \
  --banana nano-banana-2 \
  --aspect-ratio 16:9 \
  --image-size 1K \
  --output-dir generated_images

For professional assets or stronger text rendering:

bash

python agentclaw/skills/builtin_skills/image-generation/scripts/nano_banana_generate_image.py \
  --prompt "A premium magazine cover with the title AgentClaw, no other cover text" \
  --banana nano-banana-2 \
  --aspect-ratio 3:4 \
  --image-size 2K

Seedream Quick Start

bash

python agentclaw/skills/builtin_skills/image-generation/scripts/seedream_generate_image.py \
  --prompt "A cinematic wide-angle image of a vintage train bursting out of a black hole" \
  --seedream seedream-5 \
  --size 2K \
  --output-dir generated_images

For a coherent group:

bash

python agentclaw/skills/builtin_skills/image-generation/scripts/seedream_generate_image.py \
  --prompt "Generate four coherent illustrations of the same courtyard across spring, summer, autumn, and winter" \
  --seedream seedream-5 \
  --sequential-image-generation auto \
  --max-images 4 \
  --stream

For image-to-image:

bash

python agentclaw/skills/builtin_skills/image-generation/scripts/seedream_generate_image.py \
  --prompt "Use this logo as reference and create outdoor sports brand visuals" \
  --input-image logo.png \
  --seedream seedream-5 \
  --size 2K

Notes

Use one key variable per provider: OPENAI_IMAGE_KEY, GOOGLE_IMAGE_KEY, or ARK_API_KEY.
For OpenAI-compatible GPT Image services, use OPENAI_BASE_URL or pass --base-url.
For edits with reference images or masks, keep all source files local and pass their paths explicitly.
Prefer PNG for transparent or lossless assets, JPEG for faster photo-style outputs, and WebP for compact web delivery.
Do not display local paths such as generated_images/... or absolute_output_dir inside Markdown image links. The dashboard will resolve relative paths under /dashboard/, for example /dashboard/generated_images/..., which is not a served file URL. Use create_download_url, public_urls, image_markdown, or signed /api/files/...?token=... URLs for display.

Files

SKILL.md and 7 other files (scripts, references) in agentclaw/skills/builtin_skills/image-generation of Negai-ai/AgentClaw.

SKILL.md
references/nano_banana.md
references/openai.md
references/provider_contract.md
references/seedream.md
scripts/nano_banana_generate_image.py
scripts/openai_generate_image.py
scripts/seedream_generate_image.py

Open the folder on GitHubat commit 034efd1

Compare with similar skills

Image Generation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Image Generation compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Image Generation this skillNegai-ai/AgentClaw	330	—	~1.9k	Automated safety check: Notes	Apache-2.0	4 mo ago
Nano Banana Pro Prompts Recommend SkillYouMind-OpenLab/nano-banana-pro-prompts-recommend-skill	1.9k	1 repos	~4.1k	Automated safety check: Pass	None	today
AI Image Creatorcentminmod/my-claude-code-setup	2.7k	—	~8.1k	Automated safety check: Notes	MIT	3 days ago
Chatgpt Image Adkrusemediallc/arcads-claude-code	1.6k	—	~2.7k	Automated safety check: Notes	MIT	18 days ago
Zy Cinematic Realismpopopo-99/zy-cinematic-realism	570	—	~4.6k	Automated safety check: Pass	CC-BY-NC-4.0	7 days ago
ImageNexus-JPF/note-companion	870	3 repos	~3.9k	Automated safety check: Pass	MIT	4 days ago

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Works with

Questions about Image Generation

What does Image Generation do?

Generate, edit, and iterate raster images from text prompts or reference images with GPT Image, Nano Banana, or Seedream. Image Generation is an agent skill from Negai-ai/AgentClaw. Generate, edit, and iterate raster images from text prompts or reference images with GPT Image, Nano Banana, or Seedream.

When should I use Image Generation?

Image Generation fits situations like: visual asset creation; product/mockup imagery; style exploration; image transformation workflows across image provider APIs.

How do I install Image Generation in Claude Code?

Run `npx skills add Negai-ai/AgentClaw --skill image-generation -a claude-code`. Or copy the skill folder (agentclaw/skills/builtin_skills/image-generation in Negai-ai/AgentClaw) into .claude/skills/image-generation in your project. Claude Code loads it when a task matches its description.

How do I install Image Generation in Codex?

Run `npx skills add Negai-ai/AgentClaw --skill image-generation -a codex`. Or copy the skill folder (agentclaw/skills/builtin_skills/image-generation in Negai-ai/AgentClaw) into .agents/skills/image-generation in your project. Codex loads it when a task matches its description.

Can I use Image Generation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Negai-ai/AgentClaw --skill image-generation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/image-generation, .gemini/skills/image-generation, .github/skills/image-generation and .opencode/skills/image-generation in your project.

What does Image Generation need to run?

Going by SKILL.md and its folder, Image Generation needs Python for the scripts in its folder, the command-line tools its instructions call (python) and credentials named OPENAI_IMAGE_KEY, GOOGLE_IMAGE_KEY and ARK_API_KEY. Our summary lists: Python 3; A credential in OPENAI_IMAGE_KEY; A credential in GOOGLE_IMAGE_KEY.

Does Image Generation access the network?

SKILL.md names 1 domain. In commands or code: api.squarefaceicon.org; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Image Generation safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Image Generation use?

Image Generation is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Image Generation use?

About 1.9k tokens (SKILL.md is roughly 7.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.1k tokens, read only when the agent opens those files.

What are the alternatives to Image Generation?

Skills that share tags, products or a category with Image Generation: Nano Banana Pro Prompts Recommend Skill (YouMind-OpenLab/nano-banana-pro-prompts-recommend-skill, 1.9k stars), AI Image Creator (centminmod/my-claude-code-setup, 2.7k stars), Chatgpt Image Ad (krusemediallc/arcads-claude-code, 1.6k stars) and Zy Cinematic Realism (popopo-99/zy-cinematic-realism, 570 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Image Generation?

Negai-ai (a GitHub user) maintains it in Negai-ai/AgentClaw, which has 330 GitHub stars. The repository was last updated on June 8, 2026.

Source: Negai-ai/AgentClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Image Generation

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Image Generation Skill

Provider Selection

Workflow

API Key Handling

OpenAI Quick Start

Nano Banana Quick Start

Seedream Quick Start

Notes

Files

Compare with similar skills

Similar skills

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