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.
npx skills add jianshuo/claude-skills --skill wjs-syncing-multicamgit clone --depth 1 https://github.com/jianshuo/claude-skillsWrote 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/jianshuo/claude-skills/wjs-syncing-multicam)<a href="https://agentmods.dev/skills/jianshuo/claude-skills/wjs-syncing-multicam"><img src="https://agentmods.dev/badge/skills/jianshuo/claude-skills/wjs-syncing-multicam/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/jianshuo/claude-skills/wjs-syncing-multicam"><img src="https://agentmods.dev/badge/skills/jianshuo/claude-skills/wjs-syncing-multicam.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00122 | $0.03009 |
| Opus 5 | $0.00061 | $0.01504 |
| Sonnet 5 | $0.00024 | $0.00602 |
| Haiku 4.5 | $0.00012 | $0.00301 |
Grade A, and why
wjs-syncing-multicam 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.
How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
wjs-syncing-multicam
Compute a single time offset for each multi-source recording of the same event using audio cross-correlation, and emit a .sync.json sidecar next to each original. Originals are never modified, copied, or re-encoded. Downstream tools use -itsoffset to apply the offset at consume time.
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. Ensure it's installed, then drive it via its CLI:
python3 -m pip install -U polysync # needs ffmpeg/ffprobe on PATH
polysync sync REFERENCE SOURCE # align SOURCE to REFERENCE, write sidecars
polysync sync REFERENCE SOURCE --partial # source covers only part of the session
polysync verify REFERENCE SOURCE SOURCE.sync.json # independent residual check
Run one polysync sync per non-reference angle (reference first, same reference each time). The sections below document the algorithm, the sidecar schema, and the gotchas baked into the package — read them to interpret output and choose flags.
Design principle — sidecar over re-encode
Earlier versions of this skill produced *_synced.MOV files by trimming + re-encoding to bake the offset into the file. We removed that:
- Disk — a 75-min 4K shoot from 3 cameras is 60+ GB. Re-encoded synced copies double that for no information gain.
- Quality — every re-encode is lossy. The originals are the source of truth; sidecars are reversible metadata.
- Speed —
_synced.MOVgeneration took 10+ min per file on Apple Silicon; sidecar emission takes seconds. - Composability — any downstream tool (
polysync edit, NLE import, ffmpeg one-liners) reads the sidecar and applies the offset itself. No tool-specific file format lock-in.
When NOT to use
- Single-camera footage — nothing to sync to. For splitting one source into clips, use video-segmentation.
- Sources already aligned in an NLE timeline — don't fight the editor.
- For the auto-edit / cut / PiP rendering step that comes AFTER sync, use wjs-editing-multicam (consumes these sidecars).
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 · 139 lines · 122 tokens per session scan A f9d116f4c6da
wjs-syncing-multicam is a skill published in the GitHub repository jianshuo/claude-skills (129 stars, last pushed 21d ago), licensed MIT. It adds 122 tokens to every session and 3,009 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.
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