Borrowing it
Nothing to install: this file belongs to TheSmokeDev/taskchad-os. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/TheSmokeDev/taskchad-os/master/.claude/skills/video-processor/SKILL.mdgit clone --depth 1 https://github.com/TheSmokeDev/taskchad-osWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/thesmokedev/taskchad-os/video-processor)<a href="https://agentmods.dev/skills/thesmokedev/taskchad-os/video-processor"><img src="https://agentmods.dev/badge/skills/thesmokedev/taskchad-os/video-processor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/thesmokedev/taskchad-os/video-processor"><img src="https://agentmods.dev/badge/skills/thesmokedev/taskchad-os/video-processor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 68 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00136 | $0.05072 |
| Opus 5.5 | $0.00054 | $0.02029 |
| Sonnet 5.5 | $0.00027 | $0.01014 |
| Haiku 4.5 | $0.00014 | $0.00507 |
Grade A, and why
video-processor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 608 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Processor
Process video files for YouTube content creation and generate social media graphics. This skill provides four main capabilities:
- Transcription & Chapters: Convert video clips into timestamped transcripts, SRT subtitles, and AI-generated YouTube chapters
- YouTube Thumbnail Generation: Create AI-powered YouTube thumbnails with face references and style matching
- LinkedIn Post Images: Generate professional LinkedIn infographics and post images
- Generic Image Generation: Create custom images for any platform with flexible dimensions and prompts
When to Use This Skill
Use this skill when the user:
- Wants to transcribe video files or clips
- Needs to generate YouTube chapters
- Wants to regenerate chapters from existing transcripts
- Wants to create YouTube thumbnails
- Wants to create LinkedIn post images or infographics
- Wants to generate images for other platforms (Instagram, Twitter, Facebook, etc.)
- Mentions face swapping for thumbnails
- Asks about providing face or style references for graphics
Choosing the Right Image Generation Tool
The skill provides three image generation scripts. Choose based on platform and requirements:
Use thumbnail.py (YouTube thumbnails) when:
- User mentions "YouTube", "thumbnail", or "video thumbnail"
- 16:9 aspect ratio requested
- Dramatic, eye-catching style with faces desired
- Default: 1920x1080
Use linkedin-post.py (LinkedIn infographics) when:
- User mentions "LinkedIn", "LinkedIn post", or "business infographic"
- Square format infographic requested
- Professional, dark theme, no faces
- Default: 1200x1200
Use image-gen.py (generic) when:
- Custom dimensions specified (Instagram, Twitter, Facebook, etc.)
- Platform is not YouTube or LinkedIn
- User explicitly requests flexible/custom tool
- User provides full prompt with specific style requirements
- Required parameter:
--dimensions WIDTHxHEIGHT
Priority: Always prefer thumbnail.py or linkedin-post.py when the use case matches. Use image-gen.py as fallback for other platforms or custom requirements.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 608 lines · 136 tokens per session scan A ff5a4f4ffa7a
video-processor is a skill published in the GitHub repository TheSmokeDev/taskchad-os (28 stars, last pushed 23d ago), licensed MIT. It adds 136 tokens to every session and 5,072 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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