Borrowing it
Nothing to install: this file belongs to jordanurbs/venice-video-harness. 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/jordanurbs/venice-video-harness/main/.agents/skills/video-editing/SKILL.mdgit clone --depth 1 https://github.com/jordanurbs/venice-video-harnessWrote 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/jordanurbs/venice-video-harness/video-editing)<a href="https://agentmods.dev/skills/jordanurbs/venice-video-harness/video-editing"><img src="https://agentmods.dev/badge/skills/jordanurbs/venice-video-harness/video-editing/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/jordanurbs/venice-video-harness/video-editing"><img src="https://agentmods.dev/badge/skills/jordanurbs/venice-video-harness/video-editing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 findings, 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 MCP Rug Pull · line 48 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 88 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 215 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 217 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium Excessive Agency · line 208 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Agent Snooping · line 225 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 226 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00130 | $0.03134 |
| Opus 5.5 | $0.00052 | $0.01254 |
| Sonnet 5.5 | $0.00026 | $0.00627 |
| Haiku 4.5 | $0.00013 | $0.00313 |
Grade A, and why
video-editing 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 2mo 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 — 231 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Editing Pipeline
Parallel pipeline to the generation side of the harness. The generation pipeline synthesizes shots; this pipeline cuts already-existing media. They share ffmpeg and the burn-in-subtitles skill but are otherwise independent.
When to Reach For This Skill
Use the editing pipeline when the task involves existing media on disk:
- Re-cutting a Venice-generated episode because the pacing reads too long
- Trimming umms/uhs/false-starts out of a talking-head VO take
- Editing user-supplied raw footage (interview b-roll, phone takes, screen recordings) into a final cut
- Rescuing a TTS render that truncated mid-script (doubled-ellipsis bug, rule 26)
- Stitching pre-generated shots in a different order than the original storyboard
Do not reach for this skill when the task is "generate a new shot", "create a storyboard panel", or "render a video from a prompt". Those go through generate-episode-videos, storyboard-episode, or produce-episode.
Core Philosophy: Text + On-Demand Visuals
The LLM reads a 12KB takes_packed.md file — NOT the video itself. Pixels are only consulted at explicit decision points via scripts/timeline-view.ts.
Naive approach: 30 min of footage at 24fps = 43,200 frames × ~1,500 tokens each = 64M tokens of noise. This pipeline: 12KB of text + a handful of composite PNGs.
Same principle as giving an LLM a DOM rather than a screenshot. The transcript is the ground truth; visual sampling is only for ambiguous cuts, retake comparisons, and post-render QA.
The Five Steps
1. Transcribe -> per-source words.json + takes_packed.md
2. Read pack -> LLM forms a cut strategy
3. Confirm -> propose strategy, WAIT for user OK
4. Render EDL -> ffmpeg concat + 30ms audio fades
5. Self-eval -> cut-qa agent runs timeline_view at every cut boundary
-> pass: deliver final-edit.mp4
-> fail: propose fixes, re-render, loop (max 3 iterations)
Step 1 — Transcribe
npx tsx scripts/transcribe-sources.ts \
--dir output/<project>/shots \
--out output/<project>/edit/takes_packed.md \
--model base.en
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.
- 2mo ago First seen · 231 lines · 130 tokens per session scan A 9a20aa3de157
video-editing is a skill published in the GitHub repository jordanurbs/venice-video-harness (33 stars, last pushed yesterday), licensed MIT. It adds 130 tokens to every session and 3,134 once invoked, about $0.0005 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 2026-08-30.
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