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Pr Demo

CommunityPopular
mikeyobrien
pr-demo

Use when creating animated demos (GIFs) for pull requests or documentation. Covers terminal recording with asciinema and conversion to GIF/SVG for GitHub embedding.

Overview

Publishermikeyobrien
Repositoryralph-orchestrator
Skill namepr-demo
Stars
3.2K
Forks
299
Bundled files
Instructions only
LicenseMIT
Links
  • 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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by mikeyobrien on GitHub. Read the source before you install it.

Installation

Install the Pr Demo 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/mikeyobrien/ralph-orchestrator/tree/main/.claude/skills/pr-demo
  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/mikeyobrien/ralph-orchestrator.git /tmp/ralph-orchestrator
mkdir -p .claude/skills
cp -r /tmp/ralph-orchestrator/.claude/skills/pr-demo .claude/skills/pr-demo
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pr Demo 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 Pr Demo 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 Pr Demo 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.

PR Demo Creation

Overview

Create polished terminal demos for PRs using asciinema recordings converted to GIF. The workflow: script → record → convert → embed.

Tool Selection

GoalTool ChainOutput
CLI demo for GitHub PRasciinema → aggGIF (< 5MB)
Smaller file neededasciinema → svg-term-cliSVG (< 500KB)
TUI screenshottmux → freezeSVG/PNG

Default choice: asciinema + agg (best compatibility, GitHub renders GIFs natively)

Prerequisites

bash
# Install tools (macOS)
brew install asciinema
cargo install --git https://github.com/asciinema/agg
npm install -g svg-term-cli  # Optional: for SVG output

Workflow

1. Script Your Demo (REQUIRED)

Before recording, write a brief script:

markdown
## Demo: [feature name]
Duration: ~20-30 seconds

1. [0-3s] Show command being typed
2. [3-10s] Command executes, show key output
3. [10-25s] Highlight the "aha moment" - what makes this valuable
4. [25-30s] Clean exit or final state

Keep it short. 20-30 seconds max. Show ONE thing well.

2. Prepare Environment

bash
# Clean terminal state
clear
export PS1='$ '                    # Simple prompt
export TERM=xterm-256color         # Consistent colors
# Hide sensitive info (API keys, paths with usernames)

Terminal size: 100x24 (readable when scaled down)

3. Record

bash
# Record to .cast file
asciinema rec demo.cast --cols 100 --rows 24

# Execute your scripted demo
# Press Ctrl+D or type 'exit' when done

Tips:

  • Type at readable speed (not too fast)
  • Pause briefly after key moments
  • If you make a mistake, start over (editing is harder than re-recording)

4. Convert to GIF

bash
# Basic conversion (recommended)
agg demo.cast demo.gif

# With speed adjustment (1.5x faster)
agg --speed 1.5 demo.cast demo.gif

# With custom font size for readability
agg --font-size 14 demo.cast demo.gif

Alternative - SVG (smaller files):

bash
svg-term --in demo.cast --out demo.svg --window

5. Validate (Self-Validation)

Claude can self-validate demos using three approaches:

A. Automated Checks (run these first)
bash
# Check file size (must be < 5MB for GitHub)
ls -lh demo.gif

# Check recording duration from .cast metadata
head -1 demo.cast | jq '.duration // "check manually"'
B. Visual Validation (LLM-as-judge)

Extract a static frame for Claude to analyze:

bash
# Option 1: Use svg-term to render a specific timestamp (e.g., 15 seconds in)
svg-term --in demo.cast --out demo-preview.svg --at 15000

# Option 2: Use asciinema cat + freeze for a snapshot
asciinema cat demo.cast | head -500 | freeze -o demo-preview.png

# Option 3: Just convert to GIF and use the file directly
# Claude can read GIF files with the Read tool

Then ask Claude to analyze using the Read tool on the image:

Validation prompt:

Analyze this terminal demo screenshot. Check:
1. Is the text readable (not too small/blurry)?
2. Is the command being demonstrated visible?
3. Is there any sensitive info (API keys, /Users/username paths)?
4. Does the terminal look clean (simple prompt, no clutter)?
5. Is the "aha moment" visible - what value does this demo show?

Rate: PASS or FAIL with specific issues.
C. Content Validation (parse .cast file)

The .cast file is JSON lines - validate the content programmatically:

bash
# Check what commands were typed (input events)
grep '"i"' demo.cast | head -20

# Check recording duration
head -1 demo.cast | jq -r '.duration | floor'
# Should be 20-30 seconds

# Look for sensitive patterns
grep -iE '(api.?key|password|secret|/Users/[a-z])' demo.cast && echo "WARNING: Sensitive data found!"
D. Full Validation Checklist

After running the above, verify:

  • File size < 5MB (automated)
  • Duration 20-30 seconds (automated)
  • No sensitive info in .cast (automated)
  • Text readable in preview frame (visual/LLM)
  • Demo shows feature clearly (visual/LLM)
  • Clean terminal appearance (visual/LLM)

6. Embed in PR

markdown
## Demo

![feature demo](./docs/demos/feature-demo.gif)

*Shows: [one-sentence description of what the demo shows]*

Store demos in docs/demos/ or assets/ directory.

Quick Reference

SettingRecommended Value
Duration20-30 seconds
Terminal size100x24
Speed multiplier1.0-1.5x
Target file size< 2MB ideal, < 5MB max
Font size (agg)14-16

Common Mistakes

MistakeFix
Demo too longScript it first, show ONE thing
Text unreadableUse --font-size 14+, terminal 100x24
File too largeUse svg-term-cli instead, or increase speed
Cluttered terminalClean PS1, clear history, hide paths
No context in PRAdd one-line description below GIF

File Organization

docs/demos/
├── feature-name.gif      # The demo
├── feature-name.cast     # Source recording (optional, for re-rendering)
└── README.md             # Recording instructions for future maintainers

Frequently asked questions

What does the Pr Demo AI skill do?

Use when creating animated demos (GIFs) for pull requests or documentation. Covers terminal recording with asciinema and conversion to GIF/SVG for GitHub embedding.

Why use Pr Demo on TypingMind?

Because you install it once and use it with any model. Pr Demo 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 Pr Demo in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mikeyobrien/ralph-orchestrator/tree/main/.claude/skills/pr-demo. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Pr Demo?

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 Pr Demo?

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

Is the Pr Demo AI skill free?

Yes. It is published on GitHub by mikeyobrien under the MIT 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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