Agent skill

Wjs Editing Multicam

by jianshuo in jianshuo/claude-skills

A skill your agent uses when the user has 2+ recordings of the same event (each with a .sync.json sidecar from wjs-syncing-multicam) and wants them combined into a single MP4 — auto-switching…

MITAuto-check passedMedia & Creative

Install Wjs Editing Multicam

skills CLI
$ npx skills add jianshuo/claude-skills --skill wjs-editing-multicam -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jianshuo/claude-skills wjs-editing-multicam --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jianshuo/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/wjs-editing-multicam .claude/skills/wjs-editing-multicam && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
wjs-editing-multicam
GitHub stars
131
Token cost
~3k tokens
SKILL.md length
1,367 words
Files
1
Skills in repo
38
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when the user has 2+ recordings of the same event (each with a .sync.json sidecar from wjs-syncing-multicam) and wants them combined into a single MP4 — auto-switching…

  • Works in 4 steps: Color profile (Log). Sony FX3/FX6… → Orientation. Phone / vertically-mounted… → Delivery orientation. 小红书 / Reels /… → …
  • With optional picture-in-picture inset
  • SKILL.md covers Setup & commands, Preflight — ALWAYS check raw…, Editing quality — when… and What this skill IS — and IS NOT, plus 8 more sections
  • Calls ffmpeg, python3 and ffprobe

What it does

Wjs Editing Multicam is an agent skill from jianshuo/claude-skills. Use when the user has 2+ recordings of the same event (each with a .sync.json sidecar from wjs-syncing-multicam) and wants them combined into a single MP4 — auto-switching between cams second-by-second on audio energy, with optional picture-in-picture inset. Triggers — "auto-edit multicam", "做个剪辑", "切几个机位", "把这几个视频合成一个", "combine these angles", "PiP overlay".

Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Media & Creative. It works with FFmpeg. The repository describes itself as: 13 Claude Code skills for video production (transcribe / translate / dub / multicam / subtitles / reframe) + WeChat publishing. Compatible with Claude Code, OpenAI Codex CLI… The licence is MIT.

When your agent uses it

  • With optional picture-in-picture inset
  • — auto-edit multicam
  • Combine these angles

Example prompts

  • “auto-edit multicam”
  • “把这几个视频合成一个”
  • “combine these angles”
  • “/wjs-editing-multicam”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Color profile (Log). Sony FX3/FX6 default to S-Log3 / S-Gamut3.Cine — flat, grey, low-contrast. It MUST be converted to Rec.709 or it…
  2. Orientation. Phone / vertically-mounted shoots record rotated. Extract one frame per cam (ffmpeg -ss 200 -i CAM -frames:v 1 f.jpg) and…
  3. Delivery orientation. 小红书 / Reels / Shorts are vertical — and this footage is usually shot vertical. Render --width 1080 --height 1920…
  4. Staggered camera starts. Cameras rarely roll at the same instant; the sidecar delta/coverage shows it. The opening N seconds may be…

What it can do on your machine

Read from SKILL.md and the folder at commit b2690f5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • ffmpeg
    • python3
    • ffprobe

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • pypi.org
    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Wjs Editing Multicam loads about 3k tokens when it runs. Until then it costs about 96 tokens; SKILL.md has 1,367 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~96
When it runs · the whole SKILL.md, loaded when a task matches
~3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jianshuo/claude-skills at commit b2690f5, republished under its MIT licence (© jianshuo). 1,367 words, ~3,022 tokens.

Download SKILL.mdSave it as .claude/skills/wjs-editing-multicam/SKILL.md (or your agent's skills folder).
name
wjs-editing-multicam
description
Use when the user has 2+ recordings of the same event (each with a `.sync.json` sidecar from wjs-syncing-multicam) and wants them combined into a single MP4 — auto-switching between cams second-by-second on audio energy, with optional picture-in-picture inset. Triggers — "auto-edit multicam", "做个剪辑", "切几个机位", "把这几个视频合成一个", "combine these angles", "PiP overlay".

wjs-editing-multicam

Combine N synced camera angles into a single rendered MP4. Decisions are audio-energy-driven only — the cam with the loudest mic each second wins. Output is hard cuts (or hard cuts plus a corner PiP).

Setup & commands

The implementation lives in the open-source polysync pip package (https://pypi.org/project/polysync/ · https://github.com/jianshuo/polysync) — this skill no longer ships its own scripts. Install it, then drive it via its CLI:

bash
python3 -m pip install -U polysync      # needs ffmpeg/ffprobe on PATH

polysync edit        CAM_A CAM_B CAM_C --out edl.json   # build the decision list
polysync render-cuts edl.json --out out.mp4             # hard cuts
polysync render-pip  edl.json --out out.mp4 --pip bottom-right   # cuts + corner inset

edit and the renderers read each input's .sync.json automatically. Sync first with wjs-syncing-multicam (polysync sync) if the sidecars don't exist yet.

Render flags for raw camera footage (see Preflight below for when to use each):

bash
# Sony S-Log3 footage, shot vertical, FX6 cams turned on their side, for 小红书:
polysync render-cuts edl.json --out out.mp4 \
    --log slog3 \           # S-Log3/S-Gamut3.Cine -> Rec.709 grade
    --rotate 1:90 --rotate 2:90 \   # rotate cam1,cam2 90° CW (FX6 with no flag)
    --width 1080 --height 1920 --fill \   # vertical, crop-to-fill (no black bars)
    --duck-audio --audio-cams 0,1        # clean speaker-gated audio (cams 0,1 = the two lavs)

--duck-audio replaces the single-cam soundtrack with a speaker-gated mix: each moment keeps the active speaker's close mic and ducks the rest (much cleaner than a constant 2-mic sum, which piles up bleed/room tone). --audio-cams 0,1 restricts gating to the real speaker mics — always exclude the wide/room cam, whose mic sits at a similar level but is reverby and would otherwise get picked. (See the editing-quality note below for the why.)

Preflight — ALWAYS check raw footage before rendering (hard-won)

Straight-off-the-card footage renders WRONG without these checks. Spend 2 minutes here or you'll render the whole thing broken (we did).

  1. Color profile (Log). Sony FX3/FX6 default to S-Log3 / S-Gamut3.Cine — flat, grey, low-contrast. It MUST be converted to Rec.709 or it looks washed-out and broken. Check the .XML sidecar's CaptureGammaEquation (s-log3-cine) or ffprobe -show_entries stream=color_transfer. Fix: --log slog3. (Performance: the LUT is applied AFTER downscale automatically — a 3D LUT on 4K is ~4x slower than on 1080p for an identical result.)
  2. Orientation. Phone / vertically-mounted shoots record rotated. Extract one frame per cam (ffmpeg -ss 200 -i CAM -frames:v 1 f.jpg) and LOOK. Some cameras (FX3) write a rotation flag → ffmpeg auto-rotates, fine. Others (FX6 physically turned on its side) write no flag → people come out lying down. Fix per-cam: --rotate 1:90 (90 = clockwise; try 270 if upside-from-the-other-side).
  3. Delivery orientation. 小红书 / Reels / Shorts are vertical — and this footage is usually shot vertical. Render --width 1080 --height 1920 --fill. Default (1920×1080, pad) is for landscape only; mixing a portrait source into a landscape frame pillarboxes it (ugly black side bars).
  4. Staggered camera starts. Cameras rarely roll at the same instant; the sidecar delta/coverage shows it. The opening N seconds may be single-cam (only the first-rolling camera covers t=0). That's unavoidable — expect a single-cam intro of max(delta) seconds.

Editing quality — when polysync edit isn't enough

polysync edit switches to the loudest mic per second. With close, bleeding mics (each cam's mic also picks up the other speaker loudly), the close/guest mic stays loudest even when the other person talks, so the editor over-selects that cam and the cuts don't track the real speaker. Two fixes, applied by hand on the EDL when "cut to the correct speaker" matters:

  • Per-mic baseline-normalized speaker attribution. Per second, subtract each mic's own median energy, then pick whichever mic is highest relative to its own baseline → that's who's actually talking. (polysync's raw cam[k] - mean(others) doesn't remove the per-mic baseline offset, so it favors the loud mic.)
  • Cutaways for rhythm (剪辑感). Audio attribution alone gives long static holds. Cap any single shot (~8–10 s) and insert ~3 s cutaways to the listener (reaction shot) and the wide cam, alternating. The wide cam's quiet mic means the editor never picks it on energy — inject it deliberately for establishing / 整体.

What this skill IS — and IS NOT

IsIs not
Audio-energy-driven cam switchingFace / framing detection (no face_recognition, no MediaPipe)
Single-source audio (one cam's mic)Multi-mic mix / per-speaker gating
Hard cuts, with optional PiP insetCrossfades / opacity transitions / sliding animations
ffmpeg concat + overlay filter rendersHyperFrames composition / <hf-clip>
Coverage-aware (won't pick a cam outside its sidecar window)Frame-accurate beat alignment / VAD-edge cuts

If you need face tracking, fade transitions, captions, or HyperFrames composition, use the hyperframes skill on top of this skill's MP4 output.

REQUIRED INPUT

Original camera files (untouched) plus their .sync.json sidecars next to them. If sources aren't synced yet, run wjs-syncing-multicam first to write the sidecars. Missing sidecar = cam assumed at delta=0, full coverage.

polysync edit reads each sidecar for delta_seconds + overlap_in_reference, lifts the cam's audio envelope into the reference timeline, and only schedules a cam during its coverage window. polysync render-cuts / polysync render-pip apply ffmpeg -itsoffset per input using the EDL's deltas[] array.

When NOT to use

  • One source — nothing to switch between; use video-segmentation.
  • Polished NLE timeline already exists — don't fight the editor.
  • Want fade transitions / overlay captions / brand title cards — run this skill first to get the cut-down MP4, then feed it into wjs-overlaying-video or hyperframes.
Show full SKILL.md (606 more words)Show less

Pipeline

  1. Read each input's sidecar → list of delta_seconds[k] + overlap_in_reference[k].
  2. Extract per-cam mono PCM @ 16 kHz from the original file.
  3. Log-RMS envelope at 1 Hz frame rate (per-second).
  4. Lift each envelope into reference timeline by indexing at t_ref - delta_k; uncovered seconds become -inf so they're never picked.
  5. Audio source = the cam with the largest envelope spread (90th − 10th percentile over its covered seconds), with a small bonus for coverage fraction.
  6. Score per second: cam[k] - mean(other covered cams). Highest score = best active-speaker candidate.
  7. Editor decides EDL — two modes:
    • rotation (default): random dwell in [min_dwell=8, max_dwell=15] s, pick best-scoring covered cam (≠ current) at each cut.
    • greedy: hysteresis — hold current unless another cam's lookahead-window score beats it by --switch-threshold. Floor min_dwell=4, ceiling max_dwell=18. Both force-switch if the active cam exits its coverage window mid-shot. If no cam covers t=0 (overlap windows that start a few seconds in), the editor opens at the first covered second and backfills the lead-in with cam 0.
  8. Emit EDL JSON.

EDL schema (edl.json)

json
{
  "_about": "EDL produced by polysync.edit.autoedit. Times in reference timeline. Render commands apply ffmpeg -itsoffset deltas[k] per input.",
  "_help": {
    "inputs":        "Original media paths, in cam-index order (cam 0, cam 1, ...).",
    "deltas":        "Per-cam delta_seconds from each sidecar. Render uses ffmpeg -itsoffset deltas[k].",
    "duration_sec":  "Output duration in reference timeline.",
    "audio_source":  "Cam index whose audio track becomes the master. Single source — not a mix.",
    "coverage":      "[start, end] per cam in reference timeline.",
    "edl":           "List of {cam, start, end} segments. Times are reference-timeline seconds."
  },
  "inputs":       ["cam_a.MOV", "cam_b.MOV"],
  "deltas":       [0.0, 12.345],
  "duration_sec": 4512,
  "audio_source": 0,
  "coverage":     [[0.0, 4512.0], [12.345, 4499.835]],
  "edl":          [{"cam": 0, "start": 0, "end": 13}, {"cam": 1, "start": 13, "end": 28}, ...]
}

polysync edit writes _about + _help directly into the file so opening the JSON in any editor explains itself.

Render

CommandWhat it does
polysync render-cutsHard cuts only. concat filter graph over per-segment trim+scale+pad. Audio = audio_source cam, trimmed to first EDL row's start.
polysync render-pipHard cuts + corner picture-in-picture overlay. Main cam = EDL row's cam; PiP cam picked round-robin (or via per-row pip field). PiP is scaled to --pip-width (default 480 px), placed in a configurable corner with optional white border. No fade / no opacity — solid block on/off.

Both apply -itsoffset deltas[k] per input.

Brainstorm before running

Three real knobs to confirm with the user:

  • Pacing — --mode rotation (varied dwell, easier on the ear) vs --mode greedy (energy-following, snappier).
  • PiP — yes / no. If yes, which corner + width?
  • Min cut length — --min-dwell floor. 8 s default for rotation is conservative; talking-heads can go to 4.

audio_source is auto-picked; override with --audio-source <cam-index> if the auto-pick sounds wrong on a 30 s listen.

File layout

working_dir/
  cam_a.MOV                 # ORIGINAL, untouched
  cam_a.MOV.sync.json       # from wjs-syncing-multicam
  cam_b.MOV                 # ORIGINAL, untouched
  cam_b.MOV.sync.json
  edl.json                  # from `polysync edit`
  multicam_render.mp4       # from `polysync render-cuts` OR `polysync render-pip`

Common pitfalls

  • Trusting audio_source without listening. Spread + coverage is a proxy. Always sample a 30 s clip before committing — a high-spread track can still be clipped / distorted.
  • Running polysync edit on the full 75 min before tuning. Run on a 2-min slice first (ffmpeg -ss A -t 120 an extract per cam), listen, adjust --min-dwell / --mode, then commit to full length.
  • Expecting face-driven framing. This skill doesn't see the video — only the audio. If one cam is well-framed but quiet, the editor won't favor it. Use --audio-source + per-segment pip overrides as the manual escape hatch.
  • Re-rendering when sync was wrong. EDL bakes in deltas[] at edit time. If you fix the sidecars later, re-run polysync edit to regenerate the EDL before re-rendering.
  • Rendering a mid-video window straight from the long 4K originals = brutally slow. polysync render-cuts trims in the filter graph (trim=start=…) with no input -ss seek, so for a clip whose EDL starts deep in the source (e.g. a 90 s segment 28 min into a 34 min file) ffmpeg DECODES the 4K from t=0 to reach the window — ~20 min for a 92 s clip. Fix: pre-cut each cam's window first with accurate fast seek (ffmpeg -ss <start-2> -i src -ss 2 -t <dur> … — fast-seek to 2 s before, then accurate-decode 2 s), already rotated + graded + scaled to the target frame, then concat the multicam EDL on those short prepared windows (0-based times, cheap). All cams cut to the SAME reference window (source-local start = ref_start - delta_k) so they stay in sync. This is how /wjs-segmenting-video should render multicam segments — never feed a mid-video absolute-time EDL to a from-zero decode.

© jianshuo, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in wjs-editing-multicam of jianshuo/claude-skills.

Open the folder on GitHubat commit b2690f5

Compare with similar skills

Wjs Editing Multicam next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Wjs Editing Multicam compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Wjs Editing Multicam this skilljianshuo/claude-skills131—~3kAutomated safety check: PassMIT
Podcastzarazhangrui/personalized-podcast438—~2.3kAutomated safety check: NotesNone
Book Sales VideoKianzzz/book-sales-video218—~3.2kAutomated safety check: PassMIT
Frames CLIviticci/frames-cli405—~6.1kAutomated safety check: PassMIT
Video Assemblezenstory-ai/video-recap-skills561—~1.7kAutomated safety check: PassMIT
Extract Video Framesqdhenry/Claude-Command-Suite1.3k—~1.6kAutomated safety check: PassNone

Similar skills

  • Podcast

    zarazhangrui/personalized-podcast

    Generate a podcast episode from content you provide. An agent skill from zarazhangrui/personalized-podcast.

    438 GitHub stars~2.3k tokensUpdated 6 mo ago
    Media & CreativeAuto-check: notes
  • Book Sales Video

    Kianzzz/book-sales-video

    从书名或飞书多维表格中的成稿文案出发,结合微信读书资料与公开点评创作图书带货/书评短视频,并用豆包 TTS、Pexels、Codex 生图和本机 OpenChatCut 完成配音、配图、双语字幕、音效、动效、BGM、可编辑初稿与按需导出。用户提出“根据一本书做带货视频”“读取飞书文案制作图书视频”“写书评口播并自动剪成抖音视频”“仿参考样式做图书推荐短视频”时使用;仅查书、仅写普通书评或无关剪辑…

    218 GitHub stars~3.2k tokensUpdated 2 mo ago
    Media & CreativeAuto-check passed
  • Frames CLI

    viticci/frames-cli

    Frame screenshots and screen recordings with the frames CLI.

    405 GitHub stars~6.1k tokensUpdated 10 days ago
    Media & CreativeAuto-check passed
  • Video Assemble

    zenstory-ai/video-recap-skills

    合成视频解说最终成片:把旁白音频铺到源视频上,按旁白窗口压低原声,生成 SRT / ASS 字幕并可烧录, 最后做响度标准化。作为最终合成阶段使用。输入源视频、ttsmeta.json 与旁白位置; 输出 recap 成片和字幕。触发词:视频合成、混音、字幕、压字幕、assemble video、mux、ducking、subtitles、成片。

    561 GitHub stars~1.7k tokensUpdated 6 days ago
    Media & CreativeAuto-check passed
  • Extract Video Frames

    qdhenry/Claude-Command-Suite

    Extracts frames and timestamped audio segments from video files (GIF, MP4, MOV) at configurable intervals and stores them in a directory with a manifest file.

    1.3k GitHub stars~1.6k tokensUpdated 7 mo ago
    Media & CreativeAuto-check passed
  • Video Cut

    zenstory-ai/video-recap-skills

    把长视频按 Agent 选择的原片区间剪成短片。作为两阶段创作流程中的剪辑环节,读取 clipplan.json 与源视频, 输出 editedsource.mp4;随后 Agent 按输出时间线写 narration.json。支持单视频与多视频(sources manifest)拼剪, 本工具不读取、不映射旁白。

    561 GitHub stars~1.6k tokensUpdated 6 days ago
    Media & CreativeAuto-check passed

More from jianshuo/claude-skills

All 38 skills in this repo
  • Wjs Segmenting Video

    jianshuo/claude-skills

    A skill your agent uses when the user has a long-form video (interview / lecture / podcast / conversation) and a transcript SRT, and wants to extract 3–6 stand-alone topical short clips from it.

    131 GitHub stars~3.5k tokensUpdated 1 mo ago
    Auto-check passed
  • Wjs Uploading Video

    jianshuo/claude-skills

    Upload one or many videos to YouTube. An agent skill from jianshuo/claude-skills.

    131 GitHub stars~2.1k tokensUpdated 1 mo ago
    Auto-check passed
  • Wjs Converting Wp To Hugo

    jianshuo/claude-skills

    A skill your agent uses when migrating a WordPress site to a Hugo static site on GitHub Pages from a WXR export (.xml) plus the wp-content/uploads folder — preserving /archives/<id/ URLs, localizing…

    131 GitHub stars~1.8k tokensUpdated 1 mo ago
    Auto-check passed
  • Wjs Burning Subtitles

    jianshuo/claude-skills

    A skill your agent uses when the user has a video + an SRT and wants the subtitles either burned into the pixels (libass, always-visible) or soft-muxed as a togglable track.

    131 GitHub stars~3k tokensUpdated 1 mo ago
    Auto-check passed
  • Wjs Cleaning Spam

    jianshuo/claude-skills

    A skill your agent uses when the user complains about spam on his X/Twitter posts — 同城面付 / 寻固炮 / 线下上门 / 免费破处 这类引流号在他推文下刷的 emoji 垃圾回复 — and wants them removed.

    131 GitHub stars~532 tokensUpdated 1 mo ago
    Auto-check passed
  • Wjs Creating Video Book

    jianshuo/claude-skills

    A skill your agent uses when the user wants a book turned into YouTube chapter videos — 每章用 VoiceDrop 读书的有声书 mp3 做音轨,配 GPT Image 2 画面和中心思想大字,输出 1920×1080 横屏视频发 YouTube。Triggers — "把这本书做成视频"…

    131 GitHub stars~1.8k tokensUpdated 1 mo ago
    Auto-check passed

Works with

Questions about Wjs Editing Multicam

What does Wjs Editing Multicam do?

A skill your agent uses when the user has 2+ recordings of the same event (each with a .sync.json sidecar from wjs-syncing-multicam) and wants them combined into a single MP4 — auto-switching…. Wjs Editing Multicam is an agent skill from jianshuo/claude-skills.json sidecar from wjs-syncing-multicam) and wants them combined into a single MP4 — auto-switching between cams second-by-second on audio energy, with optional picture-in-picture inset.

When should I use Wjs Editing Multicam?

Wjs Editing Multicam fits situations like: with optional picture-in-picture inset; — auto-edit multicam; combine these angles.

How do I install Wjs Editing Multicam in Claude Code?

Run `npx skills add jianshuo/claude-skills --skill wjs-editing-multicam -a claude-code`. Or copy the skill folder (wjs-editing-multicam in jianshuo/claude-skills) into .claude/skills/wjs-editing-multicam in your project. Claude Code loads it when a task matches its description.

How do I install Wjs Editing Multicam in Codex?

Run `npx skills add jianshuo/claude-skills --skill wjs-editing-multicam -a codex`. Or copy the skill folder (wjs-editing-multicam in jianshuo/claude-skills) into .agents/skills/wjs-editing-multicam in your project. Codex loads it when a task matches its description.

Can I use Wjs Editing Multicam in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jianshuo/claude-skills --skill wjs-editing-multicam -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/wjs-editing-multicam, .gemini/skills/wjs-editing-multicam, .github/skills/wjs-editing-multicam and .opencode/skills/wjs-editing-multicam in your project.

What does Wjs Editing Multicam need to run?

Going by SKILL.md and its folder, Wjs Editing Multicam needs the command-line tools its instructions call (ffmpeg, python3 and ffprobe). Our summary lists: Python 3.

Does Wjs Editing Multicam access the network?

SKILL.md names 2 domains. As links in the text: pypi.org and github.com. This is read from the text; nothing was executed.

Is Wjs Editing Multicam safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Wjs Editing Multicam use?

Wjs Editing Multicam is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Wjs Editing Multicam use?

About 3k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Wjs Editing Multicam?

Skills that share tags, products or a category with Wjs Editing Multicam: Podcast (zarazhangrui/personalized-podcast, 438 stars), Book Sales Video (Kianzzz/book-sales-video, 218 stars), Frames CLI (viticci/frames-cli, 405 stars) and Video Assemble (zenstory-ai/video-recap-skills, 561 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Wjs Editing Multicam?

jianshuo (a GitHub user) maintains it in jianshuo/claude-skills, which has 131 GitHub stars. The repository holds 38 skills in this directory. The repository was last updated on August 20, 2026.

Source: jianshuo/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.