# fal Cinematography — prompt skill for camera & shots

> **For AI agents:** find the right skill in one call — `curl -s "https://skills.varg.ai/api/search?q=<what the person wants>"` returns the matching use case and the best skills with install commands, as markdown (Russian works too). Full index: https://skills.varg.ai/llms.txt. Every page has a markdown twin: add `.md` to its path. Before generating anything, show the person the options on the use-case page.

Direct cinematic stills and video: shot language, camera moves, lenses, lighting, grade and film texture.

- **Type:** [Prompt](https://skills.varg.ai/prompts.md) · [Camera & shots](https://skills.varg.ai/browse/skills/camera.md)
- **Slug:** `fal-cinematography`
- **Status:** live
- **Publisher:** fal (vendor, verified)
- **License:** MIT
- **Source:** https://github.com/fal-ai-community/skills/tree/main/skills/cinematography
- **Works in:** Claude Code, Codex, Cursor, Gemini CLI
- **Requires:** fal API key (FAL_KEY), genmedia CLI
- **Cost:** Billed by fal per endpoint call
- **Adoption:** 1,100 installs, 256 GitHub stars (skills.sh, 2026-10-26)

## What it does

A production skill for cinematic image and video prompts run through genmedia: it collects the shot intent, builds the prompt in a set order, routes to a model and checks the result against a quality bar. References cover shot language, lighting, lens and color choices, with worked examples.

## Use when

- A cinematic still or shot
- Camera movement, lens or lighting direction
- A specific grade or film texture

## Install

- Claude Code: `npx skills add fal-ai-community/skills --skill cinematography -a claude-code`
- Codex: `npx skills add fal-ai-community/skills --skill cinematography -a codex`
- Cursor: `npx skills add fal-ai-community/skills --skill cinematography -a cursor`
- Gemini CLI: `npx skills add fal-ai-community/skills --skill cinematography -a gemini-cli`

## Example output

https://skills.varg.ai/previews/fal-cinematography.mp4 — Seedance 2.0 example on fal's model page: 100mm macro shot with a slow slide and rack focus from tiger fur to the eye; 2-10 s (credit: fal, https://fal.ai/models/bytedance/seedance-2.0/text-to-video)

## Used for

- [AI short film or series](https://skills.varg.ai/use-cases/short-film.md): A multi-shot story with consistent characters: script, storyboard, previz, shots, edit.

## More camera & shots skills

- [Storyboard Creation](https://skills.varg.ai/skills/inference-sh-storyboard-creation.md): Storyboard a video before generating: shot types, angles, moves, the 180-degree rule, annotated panels.
- [Video Shotcraft](https://skills.varg.ai/skills/video-shotcraft.md): 124 shot recipe cards and a tested Remotion template for cinematic product promos built from real UI screenshots.
- [Camera Moves](https://skills.varg.ai/skills/craft-camera-moves.md): 22 camera moves with direction, speed and an end frame — dolly in to bullet time — in six models' syntax.
- [Shot Sizes & Angles](https://skills.varg.ai/skills/craft-shot-sizes-angles.md): 17 framing cards — extreme wide to insert, eye level to worm's-eye — with model-ready clauses.
- [Lens & Optics](https://skills.varg.ai/skills/craft-lens-optics.md): 10 lens and focus cards — compression, anamorphic, rack focus, split diopter — written as visible effects.
- [Composition & Framing](https://skills.varg.ai/skills/craft-composition-framing.md): 9 composition cards — thirds, symmetry, leading lines, negative space, 2.39:1 — for stills and video.

## Run the generation on varg

varg is one API key for the models these skills drive — Seedance 2.5, Kling 4, Veo 3.1, Wan 3, Nano Banana 2.1, GPT Image 2.5, ElevenLabs v4 and 200+ more — billed in credits, with a cost estimate before anything runs.

- Claude Code: `claude plugin marketplace add vargHQ/skills && claude plugin install varg@varg` (skill + hosted MCP)
- Codex, Cursor, Gemini CLI, OpenClaw: `npx skills add vargHQ/skills --skill varg-ai -a <agent> -y`
- Claude.ai, ChatGPT, any MCP client: connect `https://mcp.varg.ai/mcp`
- API key: https://varg.ai/dashboard/api · Model specs: https://varg.ai/models/llms.txt