transloadit-media-processing

github/awesome-copilot · updated Apr 8, 2026

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$npx skills add https://github.com/github/awesome-copilot --skill transloadit-media-processing
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summary

Cloud-based media processing for video, audio, images, and documents using 86+ specialized robots.

  • 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
skill.md

Transloadit Media Processing

Process, transform, and encode media files using Transloadit's cloud infrastructure. Supports video, audio, images, and documents with 86+ specialized processing robots.

When to Use This Skill

Use this skill when you need to:

  • Encode video to HLS, MP4, WebM, or other formats
  • Generate thumbnails or animated GIFs from video
  • Resize, crop, watermark, or optimize images
  • Convert between image formats (JPEG, PNG, WebP, AVIF, HEIF)
  • Extract or transcode audio (MP3, AAC, FLAC, WAV)
  • Concatenate video or audio clips
  • Add subtitles or overlay text on video
  • OCR documents (PDF, scanned images)
  • Run speech-to-text or text-to-speech
  • Apply AI-based content moderation or object detection
  • Build multi-step media pipelines that chain operations together

Setup

Option A: MCP Server (recommended for Copilot)

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

Option B: CLI

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

Core Workflows

Encode Video to HLS (Adaptive Streaming)

{
  "steps": {
    "encoded": {
      "robot": "/video/encode",
      "use": ":original",
      "preset": "hls-1080p"
    }
  }
}

Generate Thumbnails from Video

{
  "steps": {
    "thumbnails": {
      "robot": "/video/thumbs",
      "use": ":original",
      "count": 8,
      "width": 320,
      "height": 240
    }
  }
}

Resize and Watermark Images

{
  "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%"
    }
  }
}

OCR a Document

{
  "steps": {
    "recognized": {
      "robot": "/document/ocr",
      "use": ":original",
      "provider": "aws",
      "format": "text"
    }
  }
}

Concatenate Audio Clips

{
  "steps": {
    "imported": {
      "robot": "/http/import",
      "url": ["https://example.com/clip1.mp3", "https://example.com/clip2.mp3"]
    },
    "concatenated": {
      "robot": "/audio/concat",
      "use": "imported",
      "preset": "mp3"
    }
  }
}

Multi-Step Pipelines

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}"
    }
  }
}

Key Concepts

  • Assembly: A single processing job. Created via create_assembly (MCP) or assemblies create (CLI).
  • Template: A reusable set of steps stored on Transloadit. Created via create_template (MCP) or templates create (CLI).
  • Robot: A processing unit (e.g., /video/encode, /image/resize). See full list at https://transloadit.com/docs/transcoding/
  • Steps: JSON object defining the pipeline. Each key is a step name, each value configures a robot.
  • :original: Refers to the uploaded input file.

Tips

  • Use --wait with the CLI to block until processing completes.
  • Use preset values (e.g., "hls-1080p", "mp3", "webp") for common format targets instead of specifying every parameter.
  • Chain "use": "step_name" to build multi-step pipelines without intermediate downloads.
  • For batch processing, use /http/import to pull files from URLs, S3, GCS, Azure, FTP, or Dropbox.
  • Templates can include ${variables} for dynamic values passed at assembly creation time.
how to use transloadit-media-processing

How to use transloadit-media-processing on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add transloadit-media-processing
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/github/awesome-copilot --skill transloadit-media-processing

The skills CLI fetches transloadit-media-processing from GitHub repository github/awesome-copilot and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/transloadit-media-processing

Reload or restart Cursor to activate transloadit-media-processing. Access the skill through slash commands (e.g., /transloadit-media-processing) or your agent's skill management interface.

Security & Verification Notice

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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

User Story & Requirements Generation

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

Competitive Analysis

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

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

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

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ 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.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.649 reviews
  • William White· Dec 28, 2024

    Solid pick for teams standardizing on skills: transloadit-media-processing is focused, and the summary matches what you get after install.

  • Luis Li· Dec 28, 2024

    We added transloadit-media-processing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Camila Verma· Dec 16, 2024

    transloadit-media-processing has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Dhruvi Jain· Dec 4, 2024

    transloadit-media-processing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Oshnikdeep· Nov 23, 2024

    Keeps context tight: transloadit-media-processing is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Omar Zhang· Nov 19, 2024

    Registry listing for transloadit-media-processing matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Luis Thomas· Nov 19, 2024

    transloadit-media-processing fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Zara Srinivasan· Nov 7, 2024

    Useful defaults in transloadit-media-processing — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Omar Farah· Oct 26, 2024

    transloadit-media-processing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Ganesh Mohane· Oct 14, 2024

    transloadit-media-processing has been reliable in day-to-day use. Documentation quality is above average for community skills.

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