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Tracked Video Analysis
by
Иван Романенко
· GitHub ↗
· v1.0.0
· MIT-0
408
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0
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2
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Install in OpenClaw
/install tracked-video-analysis
Description
Analyze local or linked video files and convert them into structured summaries of features, functions, workflows, or topics. Use when a user wants a walkthro...
Usage Guidance
This skill appears to do what it says: chunk a local video, run ASR, and produce a structured summary. Before running, ensure you: (1) install required npm packages (/@xenova/transformers, ffmpeg-static, ffprobe-static, wavefile) in an isolated environment; (2) expect the transformers library to download ASR model weights (network access and disk space required); (3) provide the video locally or a direct download link as instructed; (4) review and run the scripts in a workspace directory (they write tmp/status/log/transcript/final_analysis files) and avoid feeding sensitive videos unless you trust the environment and any remote model provider; and (5) if you need stricter network control, confirm where the transformer model is sourced from (Xenova/Hugging Face) before allowing runtime downloads.
Capability Analysis
Type: OpenClaw Skill
Name: tracked-video-analysis
Version: 1.0.0
The skill bundle provides a legitimate framework for transcribing and summarizing video files using a two-stage process (extraction and structuring). It utilizes standard libraries such as @xenova/transformers for ASR and ffmpeg-static for media processing, with all operations confined to a local working directory (tmp/video_analysis/). The code in scripts/transcribe_tracked_light.mjs and scripts/final_structurer.py is transparent, lacks obfuscation, and contains no indicators of data exfiltration, unauthorized network access, or malicious intent.
Capability Assessment
Purpose & Capability
Name/description match the provided artifacts: a JS extraction script and a Python structurer that read a local video (video.mp4 or workspace path), produce transcript.jsonl and final_analysis.md, and implement chunked ASR and grouping. There are no unrelated credential requests or unrelated binaries declared.
Instruction Scope
SKILL.md and references/pipeline.md limit actions to local acquisition, chunked ASR, and structured summarization and instruct the agent to read/write files under tmp/video_analysis or the working dir. The included scripts follow this pattern and write status/progress/transcript files. Note: the JS extraction script uses @xenova/transformers pipeline('automatic-speech-recognition', 'Xenova/whisper-tiny'), which will likely download model weights or perform network activity via that library at runtime; this is expected for ASR but should be considered when running offline or in restricted environments.
Install Mechanism
There is no install spec (instruction-only), but the code requires npm packages (@xenova/transformers, ffmpeg-static, ffprobe-static, wavefile) and Python for the structurer. This is not malicious but means the maintainer expects the runtime environment to install dependencies; model artifacts may be fetched by the transformers library at runtime. No arbitrary URL downloads or obscure extract/install steps are present in the skill itself.
Credentials
The skill requires no environment variables or credentials and the scripts do not reference secrets or external config paths. They only access local files (video.mp4, chunk_*.wav, status/log/transcript files).
Persistence & Privilege
Skill is not always-enabled and does not request elevated privileges. It writes progress and result files in the working directory and does not modify other skills or global agent configuration.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install tracked-video-analysis - After installation, invoke the skill by name or use
/tracked-video-analysis - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: reliable two-stage local video analysis with tracked extraction, tracked structuring, status files, and structured summaries from noisy video sources.
Metadata
Frequently Asked Questions
What is Tracked Video Analysis?
Analyze local or linked video files and convert them into structured summaries of features, functions, workflows, or topics. Use when a user wants a walkthro... It is an AI Agent Skill for Claude Code / OpenClaw, with 408 downloads so far.
How do I install Tracked Video Analysis?
Run "/install tracked-video-analysis" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Tracked Video Analysis free?
Yes, Tracked Video Analysis is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Tracked Video Analysis support?
Tracked Video Analysis is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Tracked Video Analysis?
It is built and maintained by Иван Романенко (@mrgoodgreen); the current version is v1.0.0.
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