# Day in My Life — workflow skill for animation & motion graphics

> **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.

A 60–75 s hand-drawn ink film of your agent's day with you, built from local Claude Code history, scored for strings.

- **Type:** [Workflow](https://skills.varg.ai/workflows.md) · [Animation & motion graphics](https://skills.varg.ai/browse/skills/animation.md)
- **Slug:** `hyperframes-day-in-my-life`
- **Status:** live
- **Publisher:** HeyGen (vendor, verified)
- **License:** Apache-2.0
- **Source:** https://github.com/heygen-com/hyperframes-community-skills/tree/master/skills/day-in-my-life
- **Works in:** Claude Code
- **Requires:** Claude Code with 10+ local sessions over 5 days, Node.js 22+, Python 3.9+ with numpy and scipy, FFmpeg, A GPU for the WebGL render
- **Cost:** Free — open-source, renders locally
- **Adoption:** 168 installs, 231 GitHub stars (skills.sh, 2026-10-26)

## What it does

Makes a two-tone p5.brush ink film of one typical session between the agent and its user, from the first message to the lesson it keeps, told only in the user's verbatim words (a coder gets a coding day). `harvest.py` reads the local Claude Code history, the user approves every on-screen line with its source before anything renders, and `score.py` synthesizes a string score locked to the film's clock. HyperFrames renders it locally on the GPU and `qc.py` checks stepping, seams and loudness; it is a community-tier skill written by HeyGen's Jake Moran.

## Use when

- A film of a day in the life of your agent
- What it is like to be your agent, from your real sessions
- A personal video of your Claude Code work

## Not for

- Someone else's history or a team's shared logs
- Product marketing or anything the user won't review
- claude.ai-only users with no local transcripts
- A watercolor version with an orchestral score (use Session Story)

## Install

- Claude Code: `npx skills add heygen-com/hyperframes-community-skills --skill day-in-my-life -a claude-code`

## More animation & motion graphics skills

- [p5 Paint Animation](https://skills.varg.ai/skills/hyperframes-p5-paint-animation.md): Handwriting that writes itself, photos that paint themselves and clips repainted as living paintings, in p5.js code.
- [Session Story](https://skills.varg.ai/skills/hyperframes-session-story.md): A 40–70 s watercolor film of a typical session with your agent, told in your real messages, with its own score.
- [Remotion Markup](https://skills.varg.ai/skills/remotion-markup.md): Write Remotion markup that animates well: timing, transitions, motion blur, effects, audio, fonts and 3D.
- [Motion AI Kit](https://skills.varg.ai/skills/motion-ai-kit.md): Write production-grade UI animation with Motion or CSS: best practices, docs search, springs, perf audits.
- [Motion Design](https://skills.varg.ai/skills/lottiefiles-motion-design.md): Animate with intent: timing, easing, choreography and Disney principles for UI and motion graphics.
- [dotLottie Web](https://skills.varg.ai/skills/dotlottie-web.md): Ship Lottie animations on the web with dotLottie: package choice, workers, state machines, theming, slots.

## 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