Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/Belagum/promptcutWrote 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/commands/belagum/promptcut/shorts)<a href="https://agentmods.dev/commands/belagum/promptcut/shorts"><img src="https://agentmods.dev/badge/commands/belagum/promptcut/shorts.svg" alt="Measured on agentmods" 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 | $0.00018 | $0.00177 |
| Opus 5 | $0.00009 | $0.00088 |
| Sonnet 5 | $0.00004 | $0.00035 |
| Haiku 4.5 | $0.00002 | $0.00018 |
Grade A, and why
shorts 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 7d 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
Use the video-toolbox skill. Target: $ARGUMENTS
Vertical defaults: aspect 9:16, subtitles.max_chars 26, big bold subtitles,
6-10 shots of 8-14 words, music bed at -23 dB, total 25-55 seconds.
If the input is an existing video file: transcribe --granularity word, pick the
strongest self-contained stretches from the transcript, cut each one,
reframe --aspect 9:16 --mode blur, then subs-burn. Report one file per short.
If the input is a topic or script: storyboard it into plan.json, build --fake
to check the length, then build.
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.
- 7d ago First seen · 16 lines · 18 tokens per session scan A 87024baa5060
shorts is a command published in the GitHub repository Belagum/promptcut (1 stars, last pushed 11d ago), licensed MIT. It adds 18 tokens to every session and 177 once invoked, about $0.0001 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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generate-post
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