Forge Media Route Layer
0x0funky/agent-sprite-forge
Generates an image or an image-to-video clip through a configured provider API or a signed-in Codex or Grok CLI, and reports the route, file, hash and cost estimate.
Produces a personalized, broadcast-style fan-cam video from one photo of a person, using the genmedia CLI to generate a stadium frame and then animate it.
Install Sports Fan-Cam Video
$ npx skills add fal-ai-community/skills --skill fan-cam -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install fal-ai-community/skills fan-cam --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/fal-ai-community/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/fan-cam .claude/skills/fan-cam && 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 "fan-cam" agent skill from https://github.com/fal-ai-community/skills/tree/main/skills/fan-cam into .claude/skills/fan-cam/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fan-cam", 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/fal-ai-community/skills/tree/main/skills/fan-camType 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 fal-ai-community/skills --skill fan-cam -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install fal-ai-community/skills fan-cam --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fal-ai-community/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/fan-cam .agents/skills/fan-cam && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "fan-cam" agent skill from https://github.com/fal-ai-community/skills/tree/main/skills/fan-cam into .agents/skills/fan-cam/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fan-cam", 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 fal-ai-community/skills --skill fan-cam -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install fal-ai-community/skills fan-cam --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fal-ai-community/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/fan-cam .cursor/skills/fan-cam && 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 "fan-cam" agent skill from https://github.com/fal-ai-community/skills/tree/main/skills/fan-cam into .cursor/skills/fan-cam/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fan-cam", 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/fal-ai-community/skills.git --path skills/fan-cam--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 fal-ai-community/skills --skill fan-cam -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install fal-ai-community/skills fan-cam --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fal-ai-community/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/fan-cam .gemini/skills/fan-cam && 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 "fan-cam" agent skill from https://github.com/fal-ai-community/skills/tree/main/skills/fan-cam into .gemini/skills/fan-cam/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fan-cam", 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 fal-ai-community/skills fan-camInstalls 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 fal-ai-community/skills --skill fan-cam -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/fal-ai-community/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/fan-cam .github/skills/fan-cam && 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 "fan-cam" agent skill from https://github.com/fal-ai-community/skills/tree/main/skills/fan-cam into .github/skills/fan-cam/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fan-cam", 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 fal-ai-community/skills --skill fan-cam -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install fal-ai-community/skills fan-cam --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fal-ai-community/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/fan-cam .opencode/skills/fan-cam && 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 "fan-cam" agent skill from https://github.com/fal-ai-community/skills/tree/main/skills/fan-cam into .opencode/skills/fan-cam/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fan-cam", 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
fan-cam- GitHub stars
- 251
- Token cost
- ~3.2k tokens
- SKILL.md length
- 1,544 words
- Files
- 4 (incl. references)
- Skills in repo
- 16
- Repo updated
- First seen
- Licence
- None found
At a glance
Produces a personalized, broadcast-style fan-cam video from one photo of a person, using the genmedia CLI to generate a stadium frame and then animate it.
- Making a personalized sports-crowd cutaway video from a fan's photo
- SKILL.md covers References, Required inputs, Pipeline and Endpoint selection, plus 7 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Creating stadium or arena crowd reaction shots with scoreboard overlays and channel bugs
What it does
The skill turns a single photo, event details and a desired reaction into a short clip that looks like a live sports TV cutaway. The photo is treated as an identity reference, not a ready start frame. The agent first plans the prompts, then has GPT Image 2 edit the person into a realistic 16:9 broadcast scene, optionally compresses that frame, and feeds the approved frame to Kling v3 Pro image-to-video. The result is a downloaded video with a manifest.
It asks only for missing inputs that change execution: the photo path or URL, sport, matchup, venue, league, wardrobe, scoreboard idea, crowd behavior and the reaction, from excited or laughing to nervous or caught on camera. Economy, preview or native 4K output is used only when you request it; otherwise the defaults are a high-quality 3840x2160 frame and Kling v3 Pro. A local photo is uploaded once with genmedia upload and the returned URL is reused.
Three reference files cover the prompt contract, executable genmedia command patterns and sport-specific examples. The skill defers to the genmedia, model-routing, fal-prompting and genmedia-workflow skills for syntax and routing, and says not to embed private examples or local paths in prompts.
When your agent uses it
- Making a personalized sports-crowd cutaway video from a fan's photo
- Creating stadium or arena crowd reaction shots with scoreboard overlays and channel bugs
- Generating a broadcast-style screenshot of a person at a game
Example prompts
- “Make a fan-cam of me from this photo, cheering at a basketball playoff game in a packed arena.”
- “Create a nervous-reaction cutaway at a World Cup match using the photo at ./me.jpg.”
- “Generate a broadcast screenshot with a scoreboard overlay and channel bug of my friend at a baseball game.”
Requirements
- The genmedia CLI
- A photo of the person, as a local file or URL
What it can do on your machine
Read from SKILL.md and the folder at commit 9ca8504. 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
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash and json).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Sports Fan-Cam Video loads about 3.2k tokens when it runs, and up to ~8.5k if it reads all its reference files. Until then it costs about 74 tokens; SKILL.md has 1,544 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); files beside SKILL.md are not scanned.
SKILL.md
Without a licence we can't republish the file, so here is its outline and opening line. It has 1,544 words (~3,189 tokens).
“Use this skill when the user wants a personalized spectator video that feels like a real live sports broadcast cutaway. The usual input is one photo of the person, event details, and a desired reaction or situation.”
- name
- fan-cam
Files
SKILL.md and 3 other files (references) in skills/fan-cam of fal-ai-community/skills.
- SKILL.md
- references/examples.md
- references/genmedia-commands.md
- references/prompt-contract.md
Open the folder on GitHubat commit 9ca8504
Compare with similar skills
Sports Fan-Cam Video 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 |
|---|---|---|---|---|---|---|
| Sports Fan-Cam Video this skillfal-ai-community/skills | 251 | — | ~3.2k | Automated safety check: Pass | None | |
| Forge Media Route Layer0x0funky/agent-sprite-forge | 4.4k | — | ~2.2k | Automated safety check: Pass | MIT | |
| 9Router Image Generationdecolua/9router | 31k | — | ~830 | Automated safety check: Pass | MIT | |
| Shotshypersocialinc/shots | 240 | — | ~2k | Automated safety check: Pass | None | |
| Nbcraftjieyefriic/nbcraft | 155 | — | ~2.8k | Automated safety check: Pass | MIT | |
| Keirouter Imagemydisha/keirouter | 147 | — | ~691 | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Sports Fan-Cam Video
What does Sports Fan-Cam Video do?
Produces a personalized, broadcast-style fan-cam video from one photo of a person, using the genmedia CLI to generate a stadium frame and then animate it. The skill turns a single photo, event details and a desired reaction into a short clip that looks like a live sports TV cutaway. The photo is treated as an identity reference, not a ready start frame.
When should I use Sports Fan-Cam Video?
Sports Fan-Cam Video fits situations like: making a personalized sports-crowd cutaway video from a fan's photo; creating stadium or arena crowd reaction shots with scoreboard overlays and channel bugs; generating a broadcast-style screenshot of a person at a game.
How do I install Sports Fan-Cam Video in Claude Code?
Run `npx skills add fal-ai-community/skills --skill fan-cam -a claude-code`. Or copy the skill folder (skills/fan-cam in fal-ai-community/skills) into .claude/skills/fan-cam in your project. Claude Code loads it when a task matches its description.
How do I install Sports Fan-Cam Video in Codex?
Run `npx skills add fal-ai-community/skills --skill fan-cam -a codex`. Or copy the skill folder (skills/fan-cam in fal-ai-community/skills) into .agents/skills/fan-cam in your project. Codex loads it when a task matches its description.
Can I use Sports Fan-Cam Video 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 fal-ai-community/skills --skill fan-cam -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fan-cam, .gemini/skills/fan-cam, .github/skills/fan-cam and .opencode/skills/fan-cam in your project.
What does Sports Fan-Cam Video need to run?
SKILL.md names no scripts, command-line tools or credentials: Sports Fan-Cam Video is instructions for the agent only. Our summary lists: The genmedia CLI; A photo of the person, as a local file or URL.
Does Sports Fan-Cam Video access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Sports Fan-Cam Video 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. Review the folder before installing.
What licence does Sports Fan-Cam Video use?
No licence was found for Sports Fan-Cam Video or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Sports Fan-Cam Video use?
About 3.2k tokens (SKILL.md is roughly 13k 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 5.3k tokens, read only when the agent opens those files.
What are the alternatives to Sports Fan-Cam Video?
Skills that share tags, products or a category with Sports Fan-Cam Video: Forge Media Route Layer (0x0funky/agent-sprite-forge, 4.4k stars), 9Router Image Generation (decolua/9router, 31k stars), Shots (hypersocialinc/shots, 240 stars) and Nbcraft (jieyefriic/nbcraft, 155 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Sports Fan-Cam Video?
fal-ai-community (a GitHub organization) maintains it in fal-ai-community/skills, which has 251 GitHub stars. The repository holds 16 skills in this directory. The repository was last updated on September 29, 2026.
Source: fal-ai-community/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.