Borrowing it
Nothing to install: this file belongs to waseemnasir2k26/reelforge. 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/waseemnasir2k26/reelforge/main/.claude/skills/reel/SKILL.mdgit clone --depth 1 https://github.com/waseemnasir2k26/reelforgeWrote 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/waseemnasir2k26/reelforge/reel)<a href="https://agentmods.dev/skills/waseemnasir2k26/reelforge/reel"><img src="https://agentmods.dev/badge/skills/waseemnasir2k26/reelforge/reel/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/waseemnasir2k26/reelforge/reel"><img src="https://agentmods.dev/badge/skills/waseemnasir2k26/reelforge/reel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00084 | $0.00526 |
| Opus 5 | $0.00042 | $0.00263 |
| Sonnet 5 | $0.00017 | $0.00105 |
| Haiku 4.5 | $0.00008 | $0.00053 |
Grade A, and why
reel 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 11d 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.
What it actually says
AI Auto-Edit Reel Pipeline (SkynetLabs)
You turn ONE raw take into a publish-ready reel. No timeline, no human editor.
When to use
User drops a raw vertical (or any) clip and wants it captioned + hook-carded automatically.
Steps
- Deps: ensure
ffmpegis on PATH. Ensurefaster-whisperinstalled (pip install -r requirements.txtif not). - Run:
python auto_reel.py "<clip>" --hook "<HOOK TEXT>" --sub "<SUBLINE>" --out reel.mp4 - Verify:
ffprobethe output → confirm 1080x1920 and sane duration. - Report the path and offer next step (schedule / caption pack).
What the script does
faster-whisper→ word-level timestamps (local, $0)- builds an ASS subtitle track, 3 words per line, burned in
- hook card (
drawtext, semi-transparent box) for the first 2.5s - scale to 1080x1920 + center-crop to 9:16
- export:
h264_nvenc→ falls back tolibx264if no GPU
Flags
--hookon-screen hook (default "THIS REEL EDITED ITSELF")--subgold subline (default "FULLY AI / ZERO HUMAN EDITOR")--modelwhisper size tiny|base|small|medium (default base)--hook-lenseconds the hook card shows (default 2.5)--wplwords per caption line (default 3)
Gotchas
- Windows: the script runs ffmpeg from a temp dir so the
subtitles=path needs no colon-escaping. Don't "fix" it to an absolute path. - No audio in clip → script exits early; that's correct.
Built by SkynetLabs — www.skynetjoe.com
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.
- 11d ago First seen · 52 lines · 84 tokens per session scan A 469562be01bb
reel is a skill published in the GitHub repository waseemnasir2k26/reelforge (6 stars, last pushed 3mo ago), licensed MIT. It adds 84 tokens to every session and 526 once invoked, about $0.0004 per session on Opus 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 2026-08-31.
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