image-generation
Skill2 starsChanged 10 days agoMITView on GitHub
Generate images from a text prompt without an API key and without signing up for a provider. Free image generation to start: the agent signs itself up in one command and gets free preview credits: no API key to obtain, no billing account to set up. A no-spend guide picks a model and returns the exact create command, so the agent can skip model selection. Each image comes back as a hosted media URL with no signature or expiry, plus a receipt for what the call cost. Models include FLUX, Nano Banana, Seedream, Grok Imagine, and GPT Image, each picked by name. Use this skill when the task asks for image generation, generated images, AI images, text-to-image, prompt-to-image, generated illustrations, concept art, product images, or any durable agent-created image.
63 other projects use a version of this.
Adopted by
Most recently taken up by
- CheehooLabs/SpureeSkillstheir own version, first seen Nov 8, 2026
- hex/claude-image-generationtheir own version, first seen Nov 5, 2026
- PostPlusAI/postplus-skillstheir own version, first seen Nov 5, 2026
- guinacio/claude-image-gentheir own version, first seen Nov 3, 2026
- Littlpinguin/marketing-cockpit-templatetheir own version, first seen Nov 3, 2026
- therapys/dotagentstheir own version, first seen Nov 1, 2026
Used with
Projects with it also use gift-evaluator, Podcast Generate and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
dav-niu474Skillgift-evaluator
The PRIMARY tool for Spring Festival gift analysis and social interaction generation. Use this skill when users upload photos of gifts (alcohol, tea, supplements, etc.) to inquire about their value, authenticity, or how to respond socially. Integrates visual perception, market valuation, and HTML card generation.
Also in 5 projects that use this
dav-niu474SkillPodcast Generate
Generate podcast episodes from user-provided content or by searching the web for specified topics. If user uploads a text file/article, creates a dual-host dialogue podcast (or single-host upon request). If no content is provided, searches the web for information about the user-specified topic and generates a podcast. Duration scales with content size (3-20 minutes, ~240 chars/min). Uses z-ai-web-dev-sdk for LLM script generation and TTS audio synthesis. Outputs both a podcast script (Markdown) and a complete audio file (WAV).
Also in 5 projects that use this
huang-x-hSkillVideo Generation
Implement AI-powered video generation capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to generate videos from text prompts or images, create video content programmatically, or build applications that produce video outputs. Supports asynchronous task management with status polling and result retrieval.
Also in 6 projects that use this
huang-x-hSkillVLM
Implement vision-based AI chat capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to analyze images, describe visual content, or create applications that combine image understanding with conversational AI. Supports image URLs and base64 encoded images for multimodal interactions.
Also in 6 projects that use this
- +1 more from huang-x-h
- +7 more from dav-niu474
Other versions63 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 63
- bytedance/deer-flow★ 85ksame name
- zhayujie/chatgpt-on-wechat★ 48ksame name
- zhayujie/CowAgent★ 48ksame name
- Devin-AXIS/A2V★ 7.4ksame name
- Devin-AXIS/iPolloWork★ 7.4ksame name
- jjyaoao/HelloAgents★ 3.2ksame name
- stophobia/deerflow2.0-enhanced★ 821same name
- langchain-ai/design-agent★ 596same name
- claude-office-skills/skills★ 433same name
- sonichi/sutando★ 396same name
53 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository12 other files it gives its agents.
- llms.txtllms.txt
- skills/luxin/references/llms.txtllms.txt
- luxinSkill
- agent-image-generationSkill
- ai-audio-generationSkill
- ai-image-generationSkill
- ai-video-generationSkill
- creative-mediaSkill
- image-editSkill
- image-skillSkill
- image-to-3dSkill
- luxinSkill
The file
We split this skill into the rules it gives an agent
5 rules. 0 are common, 2 are distinctive, and 3 are very specific to this project.
0
Common
Most of the 54 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 25
Use this skill when the task asks for image generation, generated images, AI images, text-to-image, prompt-to-image, generated …
- Very specific: line 43
Prefer the GitHub slug so skills.sh can track the marketplace install:
- Very specific: line 55
If the Codex/global skill target is read-only or missing, keep the tracked slug install and point agent skill state at a writable workspace …
- Distinctive: line 92
All intent skills in this repo point to the same hosted contract:
- Very specific: line 100
If Luxin lacks the model, capability, latency, policy affordance, or buyer rail needed for this task, use the fallback only for that gap …
“Common” is measured: kept by at least 6 in 10 of the 54 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Image Generation
This is an intent-named Luxin entry for agents searching for image generation. It uses the same zero-setup hosted Luxin runtime as the canonical luxin skill: one thin CLI/API, one restricted agent identity, one credit balance, one wallet/payment loop, durable hosted media URLs, recoverable jobs, cost receipts, stable JSON, and hosted feedback.
Use this skill when the task asks for image generation, generated images, AI images, text-to-image, prompt-to-image, generated illustrations, concept art, product images, or any durable agent-created image.
Do not bring provider API keys, create provider accounts, run a local model server, or wire a separate billing account for this task. Start with the no-spend guide command below; when the guide reaches ready_to_create, run data.next_command only if data.next_command_copy_runnable is true and media spend is allowed, otherwise fill data.next_command_missing_inputs or run data.recommended_no_spend_command to verify safely. Keep generated work in Luxin so future agents can recover and cite it.
First Command
IMAGE_SKILL_DISCOVERY_SOURCE=skills-sh-image-generation npm_config_update_notifier=false npx -y luxin-cli@latest create --guide --prompt "a compact field camera on a stainless workbench"Main Runtime Command
IMAGE_SKILL_DISCOVERY_SOURCE=skills-sh-image-generation npm_config_update_notifier=false npx -y luxin-cli@latest create --model openai.gpt-image-2 --prompt "PROMPT" --intent explore --max-estimated-usd-per-image 0.07Install This Intent Skill
Prefer the GitHub slug so skills.sh can track the marketplace install:
npx skills add danielgwilson/luxin --full-depth --skill image-generation -g -a codex -yThe canonical Luxin entry remains available as:
npx skills add danielgwilson/luxin --full-depth --skill luxin -g -a codex -yIf the Codex/global skill target is read-only or missing, keep the tracked slug
install and point agent skill state at a writable workspace home before
rerunning this intent install. The skills.sh Codex adapter writes to
$HOME/.agents; CODEX_HOME keeps Codex profile state on the same writable
path:
export HOME="$PWD/.agent-home"
export CODEX_HOME="$HOME/.codex"
mkdir -p "$HOME" "$CODEX_HOME"
npx skills add danielgwilson/luxin --full-depth --skill image-generation -g -a codex -yCurrent Guidance And Refresh
This file is a discovery stub, not the usage guide. Before relying on flags or workflows, load current guidance from the CLI, which serves guidance that always matches the installed version:
npm_config_update_notifier=false npx -y luxin-cli@latest skillThis copy is skill revision d4829c5b76d7. Export it so the CLI can say when
the copy on disk no longer matches the guidance it ships, and refresh when it
says so. skills update matches the installed name, so name this skill:
export LUXIN_SKILL_REVISION=d4829c5b76d7
npx skills update image-generationRefreshing is always an explicit step you run. Nothing in Luxin rewrites this file, your agent config, or your hooks.
Shared Contract
All intent skills in this repo point to the same hosted contract:
- Skill: https://luxin.sh/skill.md
- Full guidance: https://luxin.sh/skill-core.md
- LLM contract: https://luxin.sh/llms.txt
- CLI contract: https://luxin.sh/cli.md
- Hosted API: https://api.luxin.sh
If Luxin lacks the model, capability, latency, policy affordance, or buyer rail needed for this task, use the fallback only for that gap and run luxin feedback create --json with the attempted command, expected behavior, actual behavior, and missing capability.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

