Beautify GitHub Readme
oil-oil/beautify-github-readme
Redesign GitHub README homepages or create project-native pure SVG, hybrid SVG-composed PNG/WebP, and opt-in animated GIF assets.
Create annotated animated GIF demos and screen recordings for pull requests and documentation.
$ npx skills add github/awesome-copilot --skill screen-recording -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install github/awesome-copilot screen-recording --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/github/awesome-copilot.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/screen-recording .claude/skills/screen-recording && 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 "screen-recording" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/screen-recording into .claude/skills/screen-recording/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "screen-recording", 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/github/awesome-copilot/tree/main/skills/screen-recordingType 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 github/awesome-copilot --skill screen-recording -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install github/awesome-copilot screen-recording --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/screen-recording .agents/skills/screen-recording && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "screen-recording" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/screen-recording into .agents/skills/screen-recording/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "screen-recording", 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 github/awesome-copilot --skill screen-recording -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install github/awesome-copilot screen-recording --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/screen-recording .cursor/skills/screen-recording && 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 "screen-recording" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/screen-recording into .cursor/skills/screen-recording/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "screen-recording", 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/github/awesome-copilot.git --path skills/screen-recording--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 github/awesome-copilot --skill screen-recording -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install github/awesome-copilot screen-recording --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/screen-recording .gemini/skills/screen-recording && 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 "screen-recording" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/screen-recording into .gemini/skills/screen-recording/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "screen-recording", 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 github/awesome-copilot screen-recordingInstalls 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 github/awesome-copilot --skill screen-recording -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/screen-recording .github/skills/screen-recording && 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 "screen-recording" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/screen-recording into .github/skills/screen-recording/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "screen-recording", 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 github/awesome-copilot --skill screen-recording -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install github/awesome-copilot screen-recording --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/screen-recording .opencode/skills/screen-recording && 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 "screen-recording" agent skill from https://github.com/github/awesome-copilot/tree/main/skills/screen-recording into .opencode/skills/screen-recording/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "screen-recording", 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.
screen-recordingCreate annotated animated GIF demos and screen recordings for pull requests and documentation.
Screen Recording is an agent skill from github/awesome-copilot, published by the product's own GitHub organization. Create annotated animated GIF demos and screen recordings for pull requests and documentation. Covers frame capture, timing, imageio-based GIF creation, and per-frame annotation workflows.
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development, covering Social media graphics and Pull requests. It works with GitHub. The repository describes itself as: Community-contributed instructions, agents, skills, and configurations to help you make the most of GitHub Copilot. The licence is MIT.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 727ff2e. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
pipplaywrightFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Screen Recording loads about 2k tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 477 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.
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.
The full file from github/awesome-copilot at commit 727ff2e, republished under its MIT licence (© github). 477 words, ~2,003 tokens.
.claude/skills/screen-recording/SKILL.md (or your agent's skills folder).Create animated GIF demos that show a feature or workflow in action — with annotations, variable timing, and proper pacing. Useful for PR descriptions, documentation, and release notes.
Use this skill when you need to:
pip install playwright Pillow imageio numpy scipy mss -q
playwright install chromiumUse Playwright to step through the interaction and capture each frame:
from playwright.async_api import async_playwright
async def record_frames(url, steps, width=1400, height=900):
"""
steps: list of dicts with 'action' (async callable taking page)
and 'name' (frame filename)
"""
async with async_playwright() as p:
browser = await p.chromium.launch()
page = await browser.new_page(viewport={"width": width, "height": height})
await page.goto(url, wait_until="networkidle")
for step in steps:
if step.get("action"):
await step["action"](page)
await page.wait_for_timeout(step.get("wait", 500))
await page.screenshot(path=step["name"])
await browser.close()Use imageio, not PIL, for GIF writing — PIL's GIF encoder merges visually similar frames, which kills animations.
import imageio.v3 as iio
from PIL import Image
import numpy as np
frames = []
durations = []
for frame_path, duration_ms in frame_list:
img = Image.open(frame_path)
frames.append(np.array(img))
durations.append(duration_ms)
iio.imwrite("demo.gif", frames, duration=durations, loop=0)Uniform timing makes everything feel either too fast or too slow. Use variable durations:
| Phase | Duration | Why |
|---|---|---|
| Fast action (typing, clicking) | 100ms | Feels natural, keeps energy |
| Pause after action | 600-800ms | Let the viewer process what happened |
| Hero/final message | 500ms+ | Main takeaway needs time to land |
Apply annotations to specific frames using the image-annotations skill:
from PIL import Image, ImageDraw, ImageFont
def annotate_frame(frame_path, annotations, out_path):
img = Image.open(frame_path)
draw = ImageDraw.Draw(img)
for ann in annotations:
# Apply annotation (rect, arrow, label, etc.)
pass
img.save(out_path)For smooth annotation appearance:
def apply_fade(base_frame, annotation_layer, alpha):
"""Blend annotation onto frame at given alpha (0.0 to 1.0)"""
blended = Image.blend(
base_frame.convert("RGBA"),
annotation_layer.convert("RGBA"),
alpha
)
return blended.convert("RGB")
# 2-frame pop-in at 10fps: 50% then 100%
faded_frames = [
apply_fade(base, annotations, 0.5), # frame 1: half opacity
apply_fade(base, annotations, 1.0), # frame 2: full opacity
]At 10fps, use 2 fade frames (0.2s total). At 30fps, use 3-4 frames. Easing curves look bad at low FPS — simple pop-in is snappier and more readable.
The annotation logic gets complex for anything beyond trivial demos. Write a dedicated script (e.g., annotate_gif.py) with functions instead of inline code. You'll iterate on timing and placement.
Always test in isolation first — don't rebuild the full demo to test a fade tweak:
# Small test GIF: 10 bare frames → fade frames → 15 hold frames
# Add a frame counter overlay for debugging:
draw.text((10, height - 30), f"F{i}/{total} a={alpha:.0%} FADE",
fill="white", font=small_font)For recording desktop apps, terminals, or anything outside a browser. Uses mss for fast screen capture.
import mss
from PIL import Image
import time
def record_gif(output_path, region=None, duration=5, fps=8):
"""Record screen region to GIF. region = {left, top, width, height} or None for full screen."""
with mss.mss() as sct:
if region is None:
region = sct.monitors[1] # primary monitor
frames = []
t_end = time.time() + duration
while time.time() < t_end:
t0 = time.time()
shot = sct.grab(region)
frames.append(Image.frombytes('RGB', shot.size, shot.rgb))
time.sleep(max(0, 1 / fps - (time.time() - t0)))
frames[0].save(output_path, save_all=True, append_images=frames[1:],
duration=int(1000 / fps), loop=0, optimize=True)
return len(frames)
record_gif('demo.gif', region={'left': 0, 'top': 0, 'width': 800, 'height': 500}, duration=3)Tested: 3s at 8fps → 24 frames, ~31KB. Keep fps ≤ 10 for reasonable file sizes.
Note: PIL.save(save_all=True) works for simple recordings but merges visually similar frames. For annotated GIFs with fade effects, use imageio.v3.imwrite instead.
# Find window rect, then record it as a GIF
# Reuse find_window() from the ui-screenshots skill
import ctypes
from ctypes import c_int, Structure, byref, windll
class RECT(Structure):
_fields_ = [('left', c_int), ('top', c_int), ('right', c_int), ('bottom', c_int)]
hwnd = find_window('My App')[0][0]
rect = RECT()
windll.user32.GetWindowRect(hwnd, byref(rect))
region = {'left': rect.left, 'top': rect.top,
'width': rect.right - rect.left, 'height': rect.bottom - rect.top}
record_gif('app-demo.gif', region=region, duration=5, fps=8)Programmatically find changed regions between frames to decide what to annotate:
import numpy as np
from scipy import ndimage
def find_changed_clusters(frame_a, frame_b, threshold=30, min_pixels=300, dilate=5):
"""Find bounding boxes of changed regions between two frames."""
diff = np.abs(frame_b.astype(float) - frame_a.astype(float)).max(axis=2)
mask = diff > threshold
dilated = ndimage.binary_dilation(mask, iterations=dilate)
labeled, n = ndimage.label(dilated)
clusters = []
for i in range(1, n + 1):
ys, xs = np.where(labeled == i)
if len(ys) < min_pixels:
continue
clusters.append((xs.min(), ys.min(), xs.max(), ys.max(), len(ys)))
return sorted(clusters, key=lambda c: -c[4]) # largest first| Format | VS Code Preview | GitHub | Browser |
|---|---|---|---|
| GIF | ✅ Animates | ✅ | ✅ |
| WebP | ⚠️ Static only | ✅ | ✅ |
| MP4 | ❌ Broken | ⚠️ | ✅ |
GIF is the only universally supported animated format across VS Code preview, GitHub markdown, and browsers.
© github, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/screen-recording of github/awesome-copilot.
Open the folder on GitHubat commit 727ff2e
Screen Recording 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 |
|---|---|---|---|---|---|---|
| Screen Recording this skillgithub/awesome-copilot | 40k | — | ~2k | Automated safety check: Pass | MIT | |
| Beautify GitHub Readmeoil-oil/beautify-github-readme | 1.8k | — | ~4.1k | Automated safety check: Pass | MIT | |
| Beautify GitHub ReadmeZergie/YAMMU | 106 | 1 repos | ~3.2k | Automated safety check: Pass | GPL-3.0 | |
| PR Babysitteropeninterpreter/openinterpreter | 69k | 3 repos | ~4.2k | Automated safety check: Pass | Apache-2.0 | |
| Check PRonyx-dot-app/onyx | 32k | 2 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Contributor-First PR MergeHKUDS/OpenHarness | 16k | 1 repos | ~847 | Automated safety check: Pass | MIT |
oil-oil/beautify-github-readme
Redesign GitHub README homepages or create project-native pure SVG, hybrid SVG-composed PNG/WebP, and opt-in animated GIF assets.
Zergie/YAMMU
Redesign GitHub README homepages or create standalone GitHub-safe SVG and animated GIF assets around a repository's real theme.
openinterpreter/openinterpreter
Watches an open GitHub pull request until it merges, handling review comments, diagnosing CI failures and retrying flaky checks along the way.
onyx-dot-app/onyx
Checks a GitHub, GitLab, or Perforce (p4) pull request (or merge request, or shelved changelist) for unresolved review comments, failing status checks, and incomplete PR descriptions.
HKUDS/OpenHarness
Merges external GitHub pull requests while keeping the original author credited, and fixes conflicts after the merge instead of rewriting the contribution.
cline/cline
Opens a GitHub pull request from your current branch with the gh CLI, after reviewing the commits and diff and gathering the details the PR needs.
github/awesome-copilot
Maps an unfamiliar codebase into seven evidence-backed documents in docs/codebase/, using a scan script and templates, for onboarding or architecture write-ups.
github/awesome-copilot
Designs Azure infrastructure from a natural-language description, or diagrams an existing resource group, then refines the design through conversation and deploys it with Bicep.
github/awesome-copilot
Generates, edits and validates draw.io files with correct mxGraph XML, covering flowcharts, architecture, sequence, ER and UML class diagrams.
github/awesome-copilot
Cleans raw credit data and screens variables before loan modeling, dropping unstable, noisy or redundant features and writing an Excel report of every step.
github/awesome-copilot
Builds a warm, browser-based daily focus board the user updates by talking to their agent, with Eisenhower priorities, a brain-dump box and kind not-today carryover.
github/awesome-copilot
End-to-end skill for building, testing, linting, versioning, and publishing a production-grade Python library to PyPI.
Works with
Categories
Create annotated animated GIF demos and screen recordings for pull requests and documentation. Screen Recording is an agent skill from github/awesome-copilot, published by the product's own GitHub organization. Create annotated animated GIF demos and screen recordings for pull requests and documentation.
Screen Recording fits situations like: tasks that involve Social media graphics; tasks that involve Pull requests.
Run `npx skills add github/awesome-copilot --skill screen-recording -a claude-code`. Or copy the skill folder (skills/screen-recording in github/awesome-copilot) into .claude/skills/screen-recording in your project. Claude Code loads it when a task matches its description.
Run `npx skills add github/awesome-copilot --skill screen-recording -a codex`. Or copy the skill folder (skills/screen-recording in github/awesome-copilot) into .agents/skills/screen-recording in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add github/awesome-copilot --skill screen-recording -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/screen-recording, .gemini/skills/screen-recording, .github/skills/screen-recording and .opencode/skills/screen-recording in your project.
Going by SKILL.md and its folder, Screen Recording needs the command-line tools its instructions call (pip and playwright). Our summary lists: Python 3.
SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
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.
Screen Recording is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2k tokens (SKILL.md is roughly 8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Screen Recording: Beautify GitHub Readme (oil-oil/beautify-github-readme, 1.8k stars), Beautify GitHub Readme (Zergie/YAMMU, 106 stars), PR Babysitter (openinterpreter/openinterpreter, 69k stars) and Check PR (onyx-dot-app/onyx, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
github (a GitHub organization, an official publisher) maintains it in github/awesome-copilot, which has 39,748 GitHub stars. The repository holds 417 skills in this directory. The repository was last updated on October 7, 2026.
Source: github/awesome-copilot on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.