Generate beautiful code snippet images using ray.so. This skill should be used when the user asks to create a code image, code screenshot, code snippet image, or wants to make their code look pretty for sharing. Saves images locally to the current working directory or a user-specified path.
npx skills add https://github.com/intellectronica/agent-skills --skill ray-so-code-snippet
Generate beautiful code snippet images using ray.so and save them locally.
agent-browser for screenshot capture (check availability first)Before proceeding, verify that agent-browser is available:
which agent-browser
If agent-browser is not found in the PATH, inform the user that this skill requires agent-browser and cannot proceed without it.
Fetch the current themes and languages from ray.so's GitHub repository using curl:
# Fetch and parse available themes
curl -s "https://raw.githubusercontent.com/raycast/ray-so/main/app/(navigation)/(code)/store/themes.ts" | grep -oE 'id:\s*"[^"]+"' | sed 's/id:\s*"//;s/"//' | sort -u
# Fetch and parse available languages
curl -s "https://raw.githubusercontent.com/raycast/ray-so/main/app/(navigation)/(code)/util/languages.ts" | grep -oE '^[[:space:]]*"?[a-zA-Z0-9+#-]+"?\s*:\s*\{' | sed 's/[[:space:]]*"//g;s/".*//;s/:.*//' | sort -u
MUST use AskUserQuestion to ask for EVERY parameter, presenting ALL available options. Ask for parameters in this order:
Present ALL available themes. In the question, list every theme fetched from step 2. Example:
Question: "Which theme would you like?"
Description: "Available themes: [list ALL themes from curl output]"
Options (pick 4 popular ones for quick select):
- breeze (default, purple gradient)
- midnight (cyan-blue)
- vercel (minimalist dark)
- sunset (warm orange)
Note: User can select "Other" to type any theme from the full list
Infer the language when possible. Skip this question if:
.py → python, .js → javascript, .ts → typescript, .rs → rust, .go → go, etc.)def/import → python, func/package → go, fn/let mut → rust)Only ask this question if the language cannot be confidently inferred:
Question: "Which language for syntax highlighting?"
Description: "Available languages: [list ALL languages from curl output]"
Options:
- auto (auto-detect)
- javascript
- python
- typescript
Note: User can select "Other" to type any language from the full list
Question: "Dark or light mode?"
Options:
- Dark mode (default)
- Light mode
Question: "Show the gradient background?"
Options:
- Yes, show background (default)
- No, transparent/minimal background
Question: "How much padding around the code?"
Options:
- 16 (compact)
- 32 (small)
- 64 (medium, default)
- 128 (large)
Question: "Show line numbers?"
Options:
- No (default)
- Yes
Question: "Add a title above the code? (e.g., filename)"
Options:
- No title (default)
- Yes, add title
If yes, ask for the title text.
Note: Do NOT ask about output path/filename. Save to the current working directory with a sensible filename (e.g., rayso-snippet.png, or based on the title if provided like fibonacci.png). Only use a different path if the user explicitly specifies one in their original request.
CRITICAL: ALL parameters must be in the URL hash (after #), NOT in the query string.
Build the URL using shell commands:
# 1. Base64 encode the code
CODE_BASE64=$(echo -n 'YOUR_CODE_HERE' | base64)
# 2. URL encode the base64 string
CODE_ENCODED=$(python3 -c "import urllib.parse; print(urllib.parse.quote('$CODE_BASE64'))")
# 3. Build the URL with ALL parameters in the hash
# Format: https://ray.so/#param1=value1¶m2=value2&code=ENCODED_CODE
# Do NOT include width parameter - let ray.so auto-size to fit content
URL="https://ray.so/#theme=THEME&padding=PADDING&background=BACKGROUND&darkMode=DARKMODE&language=LANGUAGE&code=${CODE_ENCODED}"
# Add optional parameters if needed:
# If lineNumbers: add "&lineNumbers=true" before &code=
# If title: add "&title=URL_ENCODED_TITLE" before &code=
URL Hash Parameters:
| Parameter | Values | Default |
|-----------|--------|---------|
| theme | Any theme from list | breeze |
| padding | 16, 32, 64, 128 | 64 |
| background | true, false | true |
| darkMode | true, false | true |
| language | Any language from list, or "auto" | auto |
| lineNumbers | true, false | false |
| title | URL-encoded string | (none) |
| width | Number (pixels) | auto |
| code | Base64-encoded, then URL-encoded | (required) |
Note on width: Do NOT include the width parameter unless you specifically need a fixed width. Without it, ray.so auto-sizes the frame to fit the code content, avoiding unnecessary empty space.
Example URL construction:
# For code: for i in range(23):\n print(i)
# Theme: midnight, Padding: 64, Dark mode: true, Background: true, Language: python, Title: test.py
CODE='for i in range(23):
print(i)'
CODE_BASE64=$(echo -n "$CODE" | base64)
CODE_ENCODED=$(python3 -c "import urllib.parse; print(urllib.parse.quote('$CODE_BASE64'))")
TITLE_ENCODED=$(python3 -c "import urllib.parse; print(urllib.parse.quote('test.py'))")
URL="https://ray.so/#theme=midnight&padding=64&background=true&darkMode=true&language=python&title=${TITLE_ENCODED}&code=${CODE_ENCODED}"
echo "$URL"
MUST use agent-browser (verified in Step 1). This approach uses the html-to-image library (same as ray.so's internal export) with high pixelRatio for crisp, sharp text rendering.
IMPORTANT: Always use a unique session name with --session to avoid stale session issues.
# Generate unique session name
SESSION="rayso-$(date +%s)"
# 1. Set viewport
agent-browser --session $SESSION set viewport 1400 900
# 2. Open the URL
agent-browser --session $SESSION open "$URL"
# 3. Wait for the page to fully render
agent-browser --session $SESSION wait --load networkidle
agent-browser --session $SESSION wait 3000
# 4. Load html-to-image library (same library ray.so uses internally)
agent-browser --session $SESSION eval 'new Promise((r,e)=>{const s=document.createElement("script");s.src="https://cdn.jsdelivr.net/npm/[email protected]/dist/html-to-image.js";s.onload=r;s.onerror=e;document.head.appendChild(s)})'
# 5. Capture at 4x resolution using html-to-image (produces crisp text)
agent-browser --session $SESSION eval 'htmlToImage.toPng(document.querySelector("#frame > div"),{pixelRatio:4,skipAutoScale:true})' > /tmp/rayso-dataurl-$SESSION.txt
# 6. Close the browser
agent-browser --session $SESSION close
# 7. Convert data URL to PNG file
DATAURL=$(cat /tmp/rayso-dataurl-$SESSION.txt | tr -d '"' | tr -d '\n')
echo "$DATAURL" | sed 's/data:image\/png;base64,//' | base64 -d > /path/to/output.png
# 8. Clean up temp file
rm /tmp/rayso-dataurl-$SESSION.txt
Critical notes:
html-to-image library which is what ray.so uses for its own export featurepixelRatio: 4 produces high-DPI images with crisp, sharp text (4x native resolution)Report the saved file location to the user. The task is complete - do not perform any additional checks, explorations, or verifications after the screenshot is saved.
User: "Create a code snippet image of this Python function"
def fibonacci(n):
if n <= 1:
return n
return fibonacci(n-1) + fibonacci(n-2)
which agent-browser - confirmed availablecurl -s "https://raw.githubusercontent.com/raycast/ray-so/main/app/(navigation)/(code)/store/themes.ts" | grep -oE 'id:\s*"[^"]+"' | sed 's/id:\s*"//;s/"//' | sort -u
def syntax - not asked*CODE='def fibonacci(n):
if n <= 1:
return n
return fibonacci(n-1) + fibonacci(n-2)'
CODE_BASE64=$(echo -n "$CODE" | base64)
CODE_ENCODED=$(python3 -c "import urllib.parse; print(urllib.parse.quote('$CODE_BASE64'))")
URL="https://ray.so/#theme=midnight&padding=64&background=true&darkMode=true&language=python&code=${CODE_ENCODED}"
SESSION="rayso-$(date +%s)"
agent-browser --session $SESSION set viewport 1400 900
agent-browser --session $SESSION open "$URL"
agent-browser --session $SESSION wait --load networkidle
agent-browser --session $SESSION wait 3000
# Load html-to-image library
agent-browser --session $SESSION eval 'new Promise((r,e)=>{const s=document.createElement("script");s.src="https://cdn.jsdelivr.net/npm/[email protected]/dist/html-to-image.js";s.onload=r;s.onerror=e;document.head.appendChild(s)})'
# Capture at 4x resolution
agent-browser --session $SESSION eval 'htmlToImage.toPng(document.querySelector("#frame > div"),{pixelRatio:4,skipAutoScale:true})' > /tmp/rayso-dataurl-$SESSION.txt
agent-browser --session $SESSION close
# Save as PNG
DATAURL=$(cat /tmp/rayso-dataurl-$SESSION.txt | tr -d '"' | tr -d '\n')
echo "$DATAURL" | sed 's/data:image\/png;base64,//' | base64 -d > ./fibonacci.png
rm /tmp/rayso-dataurl-$SESSION.txt
This skill uses the html-to-image library with pixelRatio: 4 to produce high-quality images with crisp, sharp text. This is the same rendering approach that ray.so uses for its built-in export feature.
Output quality:
Adjusting resolution:
pixelRatio:4 to pixelRatio:2 in the eval commandpixelRatio:6 (same as ray.so's "6x" export option)Forcing a specific width:
&width=NUMBER to the URL if you need a fixed width (e.g., for consistent sizing across multiple images)#title=filename.py&code=...#frame > div may have changed; inspect the page structure--session flagPython library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
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Take intellectronica/ray-so-code-snippet from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.