Borrowing it
Nothing to install: this file belongs to gug007/lpm. 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/gug007/lpm/main/.claude/skills/short/SKILL.mdgit clone --depth 1 https://github.com/gug007/lpmWrote 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/gug007/lpm/short)<a href="https://agentmods.dev/skills/gug007/lpm/short"><img src="https://agentmods.dev/badge/skills/gug007/lpm/short/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/gug007/lpm/short"><img src="https://agentmods.dev/badge/skills/gug007/lpm/short.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 | $0.00107 | $0.03680 |
| Opus 5.5 | $0.00043 | $0.01472 |
| Sonnet 5.5 | $0.00021 | $0.00736 |
| Haiku 4.5 | $0.00011 | $0.00368 |
Grade A, and why
short 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 yesterday.
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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Make a vertical lesson video from a topic and optional notes. It is not a trimmed YouTube lesson: the script, the pacing and the picture are built for a phone held upright with the sound possibly off.
The recorder, the voice and the mix are the lesson skill's (../lesson/scripts). Everything that skill's SKILL.md says about driving the app still holds and is not repeated here: the pristine ~/.lpm-lessons data dir, /Users/Shared/lpm-lessons workspace, the lesson control socket, real pointer and keys (s.keys("return"), never cliclick kp:), agent trust, waitFor/click/type selectors, foreground takes, the OpenAI key in the Keychain, the preflight and lint that check the Mac and the script before every take, the take folders (_takes/), the guarded agent settings and the checks after the mux (qa/report.json; the screen is read on the take's clock). The beat API is in lesson/reference/beats-api.md.
What makes it TikTok-native
- Vertical 1080x1920, 20–45 s. The app runs in a portrait window (820x1040 pt by default;
"window"in lesson.json). The window floats on a dark canvas with cyan, pink and violet glows. A virtual camera cuts a 9:16 crop from it that eases between a wide shot (the whole window width) and push-ins that follow the action. - Payoff first, and held. The video opens cold on the finished result (a later moment of the take) under the hook line and a big headline sticker. The steps come after. Frame 0 is already the payoff with text on it, so it is also the cover. The opening lines' beats are never seen, so the last of them does the setup (pick the project, start an agent).
- Don't cut away at 2 s. TikTok's retention graph for the best video so far (1.9K views) showed most viewers leaving at 0:02, the moment a one-line opening cut from the result to the app's setup. Its likes peaked at 0:01, on the result. Open on two lines over the payoff (
"open": 2, about 4–5 s): the hook, then a line that gives a reason to keep watching. - Hook in under 2.5 s. One short sentence: a problem ("Stop guessing your Claude Code limits."), a surprising fact, or a result. Never "In this video", never "Here's how to set it up in lpm". The headline sticker says what the video delivers ("Claude Code limits, right under your prompt 👀").
- Burned-in word-by-word captions. Most people watch muted. Pages of up to 3 words sit in the lower middle, heavy white with a black stroke, the spoken word in yellow,
*word*in cyan. They are timed from the voice clip's own transcript. - Numbered step stickers. A line's
"label"puts "① Open Settings" at the top of the frame until the next one. - No dead air. Lines follow each other with 140 ms gaps. Typing and agent thinking are jump-cut with
s.skip(). The voice is quick and upbeat (DEFAULT_STYLE inscripts/make.js, sped up 1.08x with pitch kept;"tempo"in lesson.json). - Ends on the result. The last line plays over the payoff shot the video opened on (it loops cleanly), with an
lpm.cxend sticker. No outro card, no "follow for part 2", no next-lesson teaser (user rule: every video stands alone). - Safe zones. Stickers, captions and push-in targets keep clear of TikTok's own UI: the top tabs, the right-hand button column, and the caption and sound area at the bottom. The review sheet draws those zones in.
What ships with it
12 files 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.
- scripts/camera.js 3.7 KB runs code
- scripts/edit.js 2.7 KB runs code
- scripts/kit.js 142 B runs code
- scripts/look.js 9.2 KB runs code
- scripts/make.js 13 KB runs code
- scripts/overlays.js 5.2 KB runs code
- scripts/rehook.sh 446 B runs code
- scripts/scan.sh 466 B runs code
- scripts/shared.js 289 B runs code
- scripts/take.sh 261 B runs code
- scripts/texttrack.js 4.3 KB runs code
- scripts/tiktokstage.js 4.4 KB runs code
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.
- yesterday Changed 3fe43c2fdb71
- 4d ago Changed · +1 lines 4ca4e48627a2
- 13d ago Changed · +1 lines 7c11b89ce562
- 23d ago First seen · 102 lines · 107 tokens per session scan A 0a06b812557e
short is a skill published in the GitHub repository gug007/lpm (145 stars, last pushed today), licensed MIT. It adds 107 tokens to every session and 3,680 once invoked, about $0.0004 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 2026-10-01.
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