Cloud-based media processing for video, audio, images, and documents using 86+ specialized robots.
Works with
Supports video encoding (HLS, MP4, WebM), thumbnail generation, image resizing/watermarking, audio transcoding, document OCR, and speech-to-text via chainable processing steps
Access via MCP server (recommended for IDE integration) or CLI; requires free Transloadit account with API credentials
Build multi-step pipelines by chaining robot operations together using the \"use\" field; reus
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiontransloadit-media-processingExecute the skills CLI command in your project's root directory to begin installation:
Fetches transloadit-media-processing from github/awesome-copilot and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate transloadit-media-processing. Access via /transloadit-media-processing in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Process, transform, and encode media files using Transloadit's cloud infrastructure. Supports video, audio, images, and documents with 86+ specialized processing robots.
Use this skill when you need to:
Add the Transloadit MCP server to your IDE config. This gives the agent direct access
to Transloadit tools (create_template, create_assembly, list_assembly_notifications, etc.).
VS Code / GitHub Copilot (.vscode/mcp.json or user settings):
{
"servers": {
"transloadit": {
"command": "npx",
"args": ["-y", "@transloadit/mcp-server", "stdio"],
"env": {
"TRANSLOADIT_KEY": "YOUR_AUTH_KEY",
"TRANSLOADIT_SECRET": "YOUR_AUTH_SECRET"
}
}
}
}
Get your API credentials at https://transloadit.com/c/-/api-credentials
If you prefer running commands directly:
npx -y @transloadit/node assemblies create \
--steps '{"encoded": {"robot": "/video/encode", "use": ":original", "preset": "hls-1080p"}}' \
--wait \
--input ./my-video.mp4
{
"steps": {
"encoded": {
"robot": "/video/encode",
"use": ":original",
"preset": "hls-1080p"
}
}
}
{
"steps": {
"thumbnails": {
"robot": "/video/thumbs",
"use": ":original",
"count": 8,
"width": 320,
"height": 240
}
}
}
{
"steps": {
"resized": {
"robot": "/image/resize",
"use": ":original",
"width": 1200,
"height": 800,
"resize_strategy": "fit"
},
"watermarked": {
"robot": "/image/resize",
"use": "resized",
"watermark_url": "https://example.com/logo.png",
"watermark_position": "bottom-right",
"watermark_size": "15%"
}
}
}
{
"steps": {
"recognized": {
"robot": "/document/ocr",
"use": ":original",
"provider": "aws",
"format": "text"
}
}
}
{
"steps": {
"imported": {
"robot": "/http/import",
"url": ["https://example.com/clip1.mp3", "https://example.com/clip2.mp3"]
},
"concatenated": {
"robot": "/audio/concat",
"use": "imported",
"preset": "mp3"
}
}
}
Steps can be chained using the "use" field. Each step references a previous step's output:
{
"steps": {
"resized": {
"robot": "/image/resize",
"use": ":original",
"width": 1920
},
"optimized": {
"robot": "/image/optimize",
"use": "resized"
},
"exported": {
"robot": "/s3/store",
"use": "optimized",
"bucket": "my-bucket",
"path": "processed/${file.name}"
}
}
}
create_assembly (MCP) or assemblies create (CLI).create_template (MCP) or templates create (CLI)./video/encode, /image/resize). See full list at https://transloadit.com/docs/transcoding/:original: Refers to the uploaded input file.--wait with the CLI to block until processing completes.preset values (e.g., "hls-1080p", "mp3", "webp") for common format targets instead of specifying every parameter."use": "step_name" to build multi-step pipelines without intermediate downloads./http/import to pull files from URLs, S3, GCS, Azure, FTP, or Dropbox.${variables} for dynamic values passed at assembly creation time.Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
github/awesome-copilot
github/awesome-copilot
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
Solid pick for teams standardizing on skills: transloadit-media-processing is focused, and the summary matches what you get after install.
We added transloadit-media-processing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
transloadit-media-processing has been reliable in day-to-day use. Documentation quality is above average for community skills.
transloadit-media-processing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: transloadit-media-processing is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for transloadit-media-processing matched our evaluation — installs cleanly and behaves as described in the markdown.
transloadit-media-processing fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Useful defaults in transloadit-media-processing — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
transloadit-media-processing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
transloadit-media-processing has been reliable in day-to-day use. Documentation quality is above average for community skills.
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