wjs-segmenting-video

wjs-segmenting-video is a skill for Claude Code, Codex from jianshuo/claude-skills. It costs 115 tokens per session (3,840 once invoked), scanned A, original, MIT.

A video-cutting workflow that reads a long interview, lecture, podcast, or conversation together with its SRT subtitle transcript, then produces 3–6 separate short clips and matching subtitle files.

In plain words
What is it for?
Use it to turn a long video with an existing transcript into raw, platform-oriented short clips for later post-production.
Why use it?
It removes the need to find topic boundaries and make each clip understandable on its own by hand. It stops before captions, covers, illustrations, calls to action, and final rendering.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: reads .claude/ paths; positional $N argument.

Good fit Use it to turn a long video with an existing transcript into raw, platform-oriented short clips for later post-production.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jianshuo/claude-skills/wjs-segmenting-video
Install

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.

Any agent
npx skills add jianshuo/claude-skills --skill wjs-segmenting-video
Clone the repo
git clone --depth 1 https://github.com/jianshuo/claude-skills

Made for: Claude Code, Codex.

Its marketplace also offers this one on its own, as the plugin wjs-segmenting-video/plugin install wjs-segmenting-video after adding the marketplace above.

Wrote 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.

agentmods badge for wjs-segmenting-video

README.md
[![agentmods](https://agentmods.dev/badge/skills/jianshuo/claude-skills/wjs-segmenting-video/github.svg)](https://agentmods.dev/skills/jianshuo/claude-skills/wjs-segmenting-video)
Your own site
<a href="https://agentmods.dev/skills/jianshuo/claude-skills/wjs-segmenting-video"><img src="https://agentmods.dev/badge/skills/jianshuo/claude-skills/wjs-segmenting-video/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.

agentmods 80×15 button for wjs-segmenting-video

Your own site · 80×15
<a href="https://agentmods.dev/skills/jianshuo/claude-skills/wjs-segmenting-video"><img src="https://agentmods.dev/badge/skills/jianshuo/claude-skills/wjs-segmenting-video.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 115 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,840 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

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 →

  • medium Rogue Agent · line 54
    Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
    Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00115 $0.03840
Opus 5 $0.00057 $0.01920
Sonnet 5 $0.00023 $0.00768
Haiku 4.5 $0.00012 $0.00384

Measured 12d ago against content hash 4e44bb44edf0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

wjs-segmenting-video 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 12d ago.

The scan reads SKILL.md. This mod also ships 5 executable files (scripts/burn_subs.py, scripts/compose_cover.py, scripts/make_cover.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

wjs-segmenting-video/SKILL.md · 302 lines

How it starts

The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.

wjs-segmenting-video

Cut a long video + SRT into multiple stand-alone short clips, each oriented for the target platform. This skill stops after cutting + cropping — it hands off the raw clips to /wjs-overlaying-video for covers, captions, illustrations, CTA, and final render.

When to use

  • Long-form video (≥10 min) with an existing SRT transcript.
  • Goal is stand-alone short clips (each viewable without context).
  • The user will (or you will) drive post-production separately in /wjs-overlaying-video.

When NOT to use

  • Single-topic trimming → just use ffmpeg -ss A -to B.
  • No transcript yet → run /wjs-transcribing-audio first (then /wjs-translating-subtitles if the segments need a non-source language).
  • Multicam editing → use /wjs-editing-multicam.
  • Highlight reel with multiple cuts inside a single topic → that's editing, not segmentation.

What this skill IS — and IS NOT

Is Is not
You (the agent) read the full SRT and decide the topic boundaries A script that runs NLP topic modeling, silence detection, or "viral moment" scoring. Topic boundaries are semantic; competing tools (Descript, OpusClip, Riverside Magic Clips) all get this wrong by automating it.
segment.py cuts; /wjs-reframing-video reorients An end-to-end "magic" pipeline
Accurate-seek cuts by default (re-encode) — clip starts EXACTLY at requested timestamp Stream-copy cuts (those produce keyframe-snap drift up to GOP duration)
Hands off raw cropped clips + per-clip SRTs Burned subtitles, covers, intros, CTAs (those live in /wjs-overlaying-video)

The pipeline

long video + SRT
   ↓     (agent reads SRT, decides topics — judgment, not parsing)
segments.json
   ↓     segment.py --reencode (accurate seek; clip starts exactly at requested t)
clip_NN.mp4 + frame_NN.jpg
   ↓     ASK: target platform orientation match source?
   ↓     /wjs-reframing-video on each clip (if 16:9 → 9:16, etc.)
   ↓     re-extract frames from cropped clips
clip_NN.mp4 (now in target orientation) + clip_NN.zh-CN.burn.srt
   ↓
HAND OFF → /wjs-overlaying-video
   (does covers + captions + illustrations + CTA + final render)

Read the full file on GitHub · 302 lines

Files

What ships with it

8 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.

Changes

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.

  1. 12d ago First seen · 302 lines · 115 tokens per session scan A 4e44bb44edf0

Subscribe to this mod's changes

wjs-segmenting-video is a skill published in the GitHub repository jianshuo/claude-skills (129 stars, last pushed 22d ago), licensed MIT. It adds 115 tokens to every session and 3,840 once invoked, about $0.0006 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 2026-08-30.

Related

Other skills, from other repositories

baoyu-comic

A tool for creating original educational comics that explain knowledge or ideas through multiple illustrated panels. It supports different art styles and tones and can create several comics in one batch.

JimLiu/baoyu-skills · 61 tokens

baoyu-danger-gemini-web

Generates images and text via reverse-engineered Gemini Web API. Supports text generation, image generation from prompts, reference images for vision input, and multi-turn conversations. Use when other skills need image generation backend, or when user requests "generate image with Gemini", "Gemini text generation"…

JimLiu/baoyu-skills · 74 tokens

create-video-seedance-2-fal

Generate a single 4-15s vertical video clip with ByteDance Seedance 2.0 reference-to-video via fal.ai. Multi-image reference (avatar + product + setting), native lip-synced VO + ambient audio (generate-audio on by default), internal multi-cut handling within one render. Routes through the GooseWorks FAL proxy (bills…

gooseworks-ai/goose-skills · 117 tokens

create-workflow-diagram

Create FigJam/Miro-style workflow diagrams as high-quality PNG images from plain-text workflow descriptions. Renders beautiful HTML diagrams with connected nodes, arrows, and labels, then screenshots them for sharing.

gooseworks-ai/goose-skills · 45 tokens

create-chatgpt-mockup

Render pixel-accurate ChatGPT mobile (iOS) screen mockups in light mode from a thread JSON. Supports user text bubbles, user image attachments, assistant markdown prose, citation chips, the OpenAI spiral logo, the Apps-SDK GPT chip in the composer, and three header styles (model-tag, plain title, "Get Plus"). Fixed…

gooseworks-ai/goose-skills · 90 tokens

render-cosmic-mythology-voiceover

Assemble a cosmic-mythology-voiceover reel from a config — a warm spoken voiceover carries the whole narrative while N curated cosmic stills are weighted beat-synced across the delivered VO duration (cutdur = VOdur times weight over the weight sum, so emotional beats hold longer), Ken-Burns-zoomed per still (scale 2x…

gooseworks-ai/goose-skills · 223 tokens