media-toolkit
Process audio and video with clipping, conversion, analysis, captions, thumbnails, GIFs, and batch utilities. Use for practical media manipulation workflows.
git clone --depth 1 https://github.com/dkyazzentwatwa/chatgpt-skills /tmp/media-toolkit && cp -r /tmp/media-toolkit/media-toolkit ~/.claude/skills/media-toolkitSKILL.md
# Media Toolkit Use this suite for practical audio and video operations that were previously spread across many narrow skills. ## Included Tools - Audio: `audio_analyzer.py`, `audio_converter.py`, `audio_normalizer.py`, `audio_trimmer.py`, `podcast_splitter.py`, `sfx_generator.py` - Video: `video_captioner.py`, `video_clipper.py`, `video_metadata_inspector.py`, `video_thumbnail_extractor.py`, `gif_workshop.py`, `thumbnail_gen.py`, `timelapse_creator.py` ## Workflow 1. Identify the medium, input format, and target output. 2. Pick the narrowest script that completes the job. 3. Keep transformations explicit: clip times, output codec, target size, caption source, or thumbnail cadence. 4. Verify output duration, dimensions, and bitrate-sensitive settings when the request depends on platform limits. ## Guardrails - Avoid recompression churn when a simple trim or extract is enough. - Call out when generated captions or “best frame” choices are heuristic.
Run multi-indicator technical analysis on crypto or market OHLCV data. Use for deterministic trend, momentum, volume, and divergence analysis.
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Process images for cleanup, conversion, metadata, comparison, icons, palettes, collages, and sprite sheets. Use for single-image or batch image workflows.
Plan and build MCP servers with agent-friendly tools, schemas, error handling, and evaluation. Use when creating or refactoring MCP integrations.
Extract text and structure from scans, images, and scanned PDFs. Use for OCR, searchable PDFs, table extraction, receipt parsing, and business card parsing.