Fal AI Media
affaan-m/ECC
Unified media generation via fal.ai MCP — image, video, and audio.
Use fal.ai for text-to-image and image-edit generation, model comparison, queue-based image workflows, and cost-aware experiment tracking with Nano Banana and GPT Image endpoints.
Install Fal AI Image
$ npx skills add chongdashu/vibejam-starter-pack --skill fal-ai-image -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install chongdashu/vibejam-starter-pack fal-ai-image --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/chongdashu/vibejam-starter-pack.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/fal-ai-image .claude/skills/fal-ai-image && rm -rf skills-srcUse ~/.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/
Install the "fal-ai-image" agent skill from https://github.com/chongdashu/vibejam-starter-pack/tree/main/.agents/skills/fal-ai-image into .claude/skills/fal-ai-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fal-ai-image", 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 install https://github.com/chongdashu/vibejam-starter-pack/tree/main/.agents/skills/fal-ai-imageType 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.
$ npx skills add chongdashu/vibejam-starter-pack --skill fal-ai-image -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install chongdashu/vibejam-starter-pack fal-ai-image --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/chongdashu/vibejam-starter-pack.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/fal-ai-image .agents/skills/fal-ai-image && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "fal-ai-image" agent skill from https://github.com/chongdashu/vibejam-starter-pack/tree/main/.agents/skills/fal-ai-image into .agents/skills/fal-ai-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fal-ai-image", 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.
$ npx skills add chongdashu/vibejam-starter-pack --skill fal-ai-image -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install chongdashu/vibejam-starter-pack fal-ai-image --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/chongdashu/vibejam-starter-pack.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/fal-ai-image .cursor/skills/fal-ai-image && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "fal-ai-image" agent skill from https://github.com/chongdashu/vibejam-starter-pack/tree/main/.agents/skills/fal-ai-image into .cursor/skills/fal-ai-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fal-ai-image", 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 https://github.com/chongdashu/vibejam-starter-pack.git --path .agents/skills/fal-ai-image--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add chongdashu/vibejam-starter-pack --skill fal-ai-image -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install chongdashu/vibejam-starter-pack fal-ai-image --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/chongdashu/vibejam-starter-pack.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/fal-ai-image .gemini/skills/fal-ai-image && rm -rf skills-srcUse ~/.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/
Install the "fal-ai-image" agent skill from https://github.com/chongdashu/vibejam-starter-pack/tree/main/.agents/skills/fal-ai-image into .gemini/skills/fal-ai-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fal-ai-image", 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.
$ gh skill install chongdashu/vibejam-starter-pack fal-ai-imageInstalls 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).
$ npx skills add chongdashu/vibejam-starter-pack --skill fal-ai-image -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/chongdashu/vibejam-starter-pack.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/fal-ai-image .github/skills/fal-ai-image && rm -rf skills-srcUse ~/.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/
Install the "fal-ai-image" agent skill from https://github.com/chongdashu/vibejam-starter-pack/tree/main/.agents/skills/fal-ai-image into .github/skills/fal-ai-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fal-ai-image", 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.
$ npx skills add chongdashu/vibejam-starter-pack --skill fal-ai-image -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install chongdashu/vibejam-starter-pack fal-ai-image --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/chongdashu/vibejam-starter-pack.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/fal-ai-image .opencode/skills/fal-ai-image && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "fal-ai-image" agent skill from https://github.com/chongdashu/vibejam-starter-pack/tree/main/.agents/skills/fal-ai-image into .opencode/skills/fal-ai-image/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fal-ai-image", 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
fal-ai-image- GitHub stars
- 149
- Token cost
- ~1.9k tokens
- SKILL.md length
- 924 words
- Files
- 11 (incl. scripts, references, assets)
- Skills in repo
- 11
- Repo updated
- First seen
- Licence
- None found
At a glance
Use fal.ai for text-to-image and image-edit generation, model comparison, queue-based image workflows, and cost-aware experiment tracking with Nano Banana and GPT Image endpoints.
- Works in 4 steps: Queue-first for tracked experiments:… → Reference discipline matters: editing… → Prompt parity beats fake parity: keep… → …
- Tasks that involve Image generation
- SKILL.md covers Philosophy: Standardize The…, What This Skill Provides, Working With fal Images In… and Scripts, plus 4 more sections
- Runs Python scripts from its folder; calls uv; reaches queue.fal.run; needs FAL_KEY
What it does
Fal AI Image is an agent skill from chongdashu/vibejam-starter-pack. Use fal.ai for text-to-image and image-edit generation, model comparison, queue-based image workflows, and cost-aware experiment tracking with Nano Banana and GPT Image endpoints.
Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 14 other files, including scripts, reference files and assets (for example `assets/model-presets.json`, `references/fal-image-models.md` and `references/fal-platform-notes.md`).
It sits in Media & Creative, covering Image generation. It works with fal and Google Gemini. The repository describes itself as: Free Vibe Jam starter pack — battle-tested ThreeJS and Phaser agent skills, starter projects, and prompts.
When your agent uses it
- Tasks that involve Image generation
Example prompts
- “/fal-ai-image”
Requirements
- Python 3
- A credential in FAL_KEY
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Queue-first for tracked experiments: image calls can be synchronous, but queue mode gives request IDs, polling, and consistent logging.
- Reference discipline matters: editing runs should pass only the images the model actually needs; too many references dilute control.
- Prompt parity beats fake parity: keep the task stable, then document the real model-specific compromises.
- Tracking is part of the run: a generation is not complete until prompt, request metadata, outputs, and cost signals are recorded.
What it can do on your machine
Read from SKILL.md and the folder at commit 6793771. 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 4 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
uv
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:
queue.fal.run
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
FAL_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Fal AI Image loads about 1.9k tokens when it runs, and up to ~3.5k if it reads all its reference files. Until then it costs about 48 tokens; SKILL.md has 924 words of instructions outside code blocks.
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 passed
The automated check found no risky patterns in SKILL.md.
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
Without a licence we can't republish the file, so here is its outline and opening line. It has 924 words (~1,903 tokens).
“Use this skill when the user wants to generate or edit images through fal.ai, compare multiple marketplace image models, or build repeatable experiment workflows with prompts, references, outputs, and costs tracked in a consistent way.”
- name
- fal-ai-image
- metadata.short-description
- fal.ai image generation, editing, and comparison.
Files
SKILL.md and 10 other files (scripts, references, assets) in .agents/skills/fal-ai-image of chongdashu/vibejam-starter-pack.
- SKILL.md
- assets/model-presets.json
- assets/prompt-profiles/pirate-character-edit-v1.txt
- assets/prompt-profiles/pirate-character-render-v1.txt
- references/fal-image-models.md
- references/fal-platform-notes.md
- references/fal-queue-and-inference.md
- scripts/_fal_common.py
- scripts/fal_image_experiment_matrix.py
- scripts/fal_platform_models.py
- scripts/fal_queue_image_run.py
Open the folder on GitHubat commit 6793771
Compare with similar skills
Fal AI Image 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Fal AI Image this skillchongdashu/vibejam-starter-pack | 149 | — | ~1.9k | Automated safety check: Pass | None | |
| Fal AI Mediaaffaan-m/ECC | 276k | 4 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Fal AI Mediaaffaan-m/ECC | 276k | 2 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Fal AI Mediaaffaan-m/ECC | 276k | — | ~1.4k | Automated safety check: Pass | MIT | |
| Fal AI Imageartwist-polyakov/polyakov-claude-skills | 208 | — | ~2.1k | Automated safety check: Notes | MIT | |
| Model Routingfal-ai-community/skills | 251 | — | ~1.5k | Automated safety check: Pass | None |
Similar skills
Fal AI Media
affaan-m/ECC
通过 fal.ai MCP 实现统一的媒体生成——图像、视频和音频。涵盖文本到图像（Nano Banana）、文本/图像到视频（Seedance、Kling、Veo 3）、文本到语音（CSM-1B），以及视频到音频（ThinkSound）。当用户想要使用 AI 生成图像、视频或音频时使用。
Fal AI Media
affaan-m/ECC
fal.ai MCPによる統合メディア生成（画像、動画、音声）。テキストから画像（Nano Banana）、テキスト/画像から動画（Seedance、Kling、Veo 3）、テキストから音声（CSM-1B）、動画から音声（ThinkSound）をカバーします。ユーザーがAIで画像、動画、音声を生成したい場合に使用します。
Fal AI Image
artwist-polyakov/polyakov-claude-skills
Generate/edit images via fal.ai. An agent skill from artwist-polyakov/polyakov-claude-skills.
Model Routing
fal-ai-community/skills
Choose default fal.ai endpoint IDs for genmedia production skills.
Nano Banana Pro Prompting
nodetool-ai/nodetool
Prompt Google's Nano Banana Pro image model — the art-director brief it plans against, the lock/change/amount/constraints shape every edit needs, and the patterns for typography, diagrams, product…
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Related
Works with
Categories
Questions about Fal AI Image
What does Fal AI Image do?
Use fal.ai for text-to-image and image-edit generation, model comparison, queue-based image workflows, and cost-aware experiment tracking with Nano Banana and GPT Image endpoints. Fal AI Image is an agent skill from chongdashu/vibejam-starter-pack.ai for text-to-image and image-edit generation, model comparison, queue-based image workflows, and cost-aware experiment tracking with Nano Banana and GPT Image endpoints.
When should I use Fal AI Image?
Fal AI Image fits situations like: tasks that involve Image generation.
How do I install Fal AI Image in Claude Code?
Run `npx skills add chongdashu/vibejam-starter-pack --skill fal-ai-image -a claude-code`. Or copy the skill folder (.agents/skills/fal-ai-image in chongdashu/vibejam-starter-pack) into .claude/skills/fal-ai-image in your project. Claude Code loads it when a task matches its description.
How do I install Fal AI Image in Codex?
Run `npx skills add chongdashu/vibejam-starter-pack --skill fal-ai-image -a codex`. Or copy the skill folder (.agents/skills/fal-ai-image in chongdashu/vibejam-starter-pack) into .agents/skills/fal-ai-image in your project. Codex loads it when a task matches its description.
Can I use Fal AI Image 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 chongdashu/vibejam-starter-pack --skill fal-ai-image -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fal-ai-image, .gemini/skills/fal-ai-image, .github/skills/fal-ai-image and .opencode/skills/fal-ai-image in your project.
What does Fal AI Image need to run?
Going by SKILL.md and its folder, Fal AI Image needs Python for the scripts in its folder, the command-line tools its instructions call (uv) and credentials named FAL_KEY. Our summary lists: Python 3; A credential in FAL_KEY.
Does Fal AI Image access the network?
SKILL.md names 1 domain. In commands or code: queue.fal.run; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Fal AI Image safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. 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 Fal AI Image use?
No licence was found for Fal AI Image or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Fal AI Image use?
About 1.9k tokens (SKILL.md is roughly 7.6k 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 1.6k tokens, read only when the agent opens those files.
What are the alternatives to Fal AI Image?
Skills that share tags, products or a category with Fal AI Image: Fal AI Media (affaan-m/ECC, 276k stars), Fal AI Media (affaan-m/ECC, 276k stars), Fal AI Media (affaan-m/ECC, 276k stars) and Fal AI Image (artwist-polyakov/polyakov-claude-skills, 208 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Fal AI Image?
chongdashu (a GitHub user) maintains it in chongdashu/vibejam-starter-pack, which has 149 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on April 15, 2026.
Source: chongdashu/vibejam-starter-pack on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.