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Session Story

Organization
heygen-com
session-story

An agent makes an animated film of an average session with its own user, beginning to end, told with that user's real messages: whatever their routine is (code, writing, data, design, video). The agent sits at a desk in a room decorated from what it knows about the user, and the monitor shows their kind of work. Requests glide in as paper planes and unfold. Corrections are a 3D cartoon mallet that bonks, then turns to show the words on its face. Praise is a butterfly towing the words on a ribbon. The agent types each reply onto a sheet, folds it and throws it back. The film opens with the agent asleep until the monitor boots: "Initiating session with <name>". The agent composes its own orchestral score, cued to every action. p5.brush watercolour, rendered in HyperFrames. Trigger on: "a video of our session", "animate a session with me", "session story", "show what working with me is like", "make a film about me and my agent".

Overview

Publisherheygen-com
Repositoryhyperframes-community-skills
Skill namesession-story
Stars
226
Forks
22
Bundled files
34
LicenseApache-2.0
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 34 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by heygen-com on GitHub. Read the source before you install it.

Installation

Install the Session Story AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/heygen-com/hyperframes-community-skills/tree/master/skills/session-story
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/heygen-com/hyperframes-community-skills.git /tmp/hyperframes-community-skills
mkdir -p .claude/skills
cp -r /tmp/hyperframes-community-skills/skills/session-story .claude/skills/session-story
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Session Story in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Session Story on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Session Story is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Session story

The agent reads its own history with its user, finds their routine, and turns one typical session into a 40 to 70 s film, in the order it happened:

  • Story: the user's verbatim words arriving as objects, and the agent's own replies going back. The window and the wall clock follow the session's real time.
  • Room: decorated from what the agent knows about its user.
  • Score: composed by the agent against the film's own timeline.

Write story.json and the engine does the choreography. Nothing on screen is invented: every line is a quote, and the user approves every line before a frame is rendered.

When to use / when not

  • Use when a user asks their agent for a film of their work together, and the agent has real history with that user: local transcripts, or messages the user pastes in.
  • Do not use for someone else's history, a team's shared logs, marketing with made-up quotes, or anything the user won't review. With no history at all, ask the user for a session's messages. Never invent quotes.

Requirements and side effects (complete list)

  • Tools: Node 22+, Python 3.9+ (standard library only), ffmpeg on PATH, and the HyperFrames CLI pinned to npx --yes hyperframes@0.8.71 (downloaded from the npm registry on first use).
  • Setup (once, manually): sh scripts/setup.sh runs npm ci from the committed lockfile: p5 2.3.3 (LGPL-2.1), p5.brush 2.2.3 (MIT), @fontsource/permanent-marker 5.3.0 (Apache-2.0). Read-only downloads from npm.
  • Score renderer: on macOS, swift (Xcode Command Line Tools) plays the score through Apple's built-in General MIDI bank. Elsewhere, fluidsynth with a General MIDI soundfont you set as SOUNDFONT. Neither downloads anything.
  • Reads (local only, after the user says yes): the agent's own transcripts, ~/.claude/projects/<project>/*.jsonl (Claude Code) and ~/.codex/sessions (Codex), for the current project unless the user allows --all-projects. Also the agent's memory and instruction files for the room. Nothing is uploaded.
  • Writes: session-story-candidates.json (harvest) and everything inside the project folder you create. Both hold the user's words: never commit or share them.
  • Network at build time: none. Pass --describe false to every snapshot, as shown below: with GEMINI_API_KEY set, snapshot otherwise sends frames (the user's words) to Gemini. Render locally: the page paints with WebGL.
  • No credentials, no paid calls.

Workflow

  1. Setup: sh scripts/setup.sh (once).
  2. Ask first. Tell the user you'll read your local history with them to find the session, and wait for a yes.
  3. Harvest: python3 scripts/harvest.py --project <their project folder> --out <scratch>/candidates.json prints the routine and lists sessions, most typical first. --session <id> (with the same --project) prints one in order, with local times and your replies. Per references/sources.md.
  4. Scaffold: node scripts/new-project.mjs <dir>. Everything you write from here lives in <dir>.
  5. Story: take a typical session and write <dir>/story.json beat by beat, in the order it happened, with each beat's real time, per references/story.md. The user's lines are verbatim spans; your replies are your own words from that session. Set screen to what their work looks like, and pick the ending their sessions have. node scripts/schedule.mjs <dir> checks it: run it after every edit.
  6. Room: fill the slots from what you know about the user, per references/room.md. Draw a custom prop in <dir>/scenes/props-custom.js when the library has nothing true to them. If you are not Claude, draw yourself: references/cast.md.
  7. Privacy gate: show the user one table of every on-screen line (hook, nameplate, each quote, each reply, each prop and why), each with its source. Take their edits, get an explicit yes, then set "approved": true. Until then every frame carries a DRAFT stamp.
  8. Design pass: run the snapshot command schedule.mjs prints. Look at every frame: quotes legible, props where they belong, nothing covering a message. Show the user the contact sheet.
  9. Score: write <dir>/score/score.py with your own theme, key and palette, per references/score.md. Then sh <dir>/score/build.sh. It fails on dead air.
  10. Render: from <dir>: npx --yes hyperframes@0.8.71 check, then npx --yes hyperframes@0.8.71 render --fps 24 --crf 12 -o renders/session-story.mp4.
  11. Check the render: its length must match schedule.mjs. Pull a frame at each key moment (ffmpeg -ss <t> -i renders/session-story.mp4 -frames:v 1 renders/check-<t>.png) and look at them. Then hand it to the user to watch with sound.

The example (node scripts/new-project.mjs <dir> --example, then schedule.mjs <dir> --example) is the reference film: a real session between Claude and the skill's author, who makes videos. It shows the format, not the shape of your film. schedule.mjs refuses it without --example, so it can't stand in for your user's story.

Verify success

  • schedule.mjs exits 0 and prints no warnings. hyperframes check passes. p5.brush logs WebGL uniform warnings, which are harmless.
  • The design-pass frames show every quote legible, and match the beat table.
  • score/build.sh ends with ok: no dead air, and the score's length matches the film's.
  • The render is the length schedule.mjs printed, has an audio track, and its frames at the key moments match the design pass.
  • Failure path to test: a story that opens on a reply, or has a quote over the limit, makes schedule.mjs exit 1 and name the beat.

What the engine owns

The motion is physical and already tuned: glide paths, the fold, the throw, the swing, the bonk and the wingbeats. Change the story, the room, the cast and the score. Leave the choreography in scenes/director.js and scenes/compile.js alone unless you are fixing a bug. The motion rules are in references/motion.md.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Session Story AI skill do?

An agent makes an animated film of an average session with its own user, beginning to end, told with that user's real messages: whatever their routine is (code, writing, data, design, video). The agent sits at a desk in a room decorated from what it knows about the user, and the monitor shows their kind of work. Requests glide in as paper planes and unfold. Corrections are a 3D cartoon mallet that bonks, then turns to show the words on its face. Praise is a butterfly towing the words on a ribbon. The agent types each reply onto a sheet, folds it and throws it back. The film opens with the a...

Why use Session Story on TypingMind?

Because you install it once and use it with any model. Session Story is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Session Story in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/heygen-com/hyperframes-community-skills/tree/master/skills/session-story. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Session Story?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Session Story?

As many as you like. As long as a model supports skills, you can use Session Story with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Session Story AI skill free?

Yes. It is published on GitHub by heygen-com under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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