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 jtydhr88/ComfyTV --skill video-editorgit clone --depth 1 https://github.com/jtydhr88/ComfyTVWrote 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/jtydhr88/comfytv/video-editor)<a href="https://agentmods.dev/skills/jtydhr88/comfytv/video-editor"><img src="https://agentmods.dev/badge/skills/jtydhr88/comfytv/video-editor/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/jtydhr88/comfytv/video-editor"><img src="https://agentmods.dev/badge/skills/jtydhr88/comfytv/video-editor.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 | $0.00111 | $0.01731 |
| Opus 5 | $0.00056 | $0.00865 |
| Sonnet 5 | $0.00022 | $0.00346 |
| Haiku 4.5 | $0.00011 | $0.00173 |
Grade A, and why
video-editor 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 5d 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Editor
Purpose
Edit existing footage by conversation. The material is the user's — takes, renders, downloads, generated clips. The job is editorial: what to keep, where to cut, how to pace, how it should look. Everything is built as stages on the user's canvas, so every decision stays visible and adjustable after you leave.
Invoke with $video-editor or infer from an editing request. Do not widen the
task into generating new footage unless asked — generation is the Director
stage's job, editing is yours.
Core principle: read the video, don't watch it
Never scan a video by pulling frames one by one. Read it through
media_timeline: one composite image of evenly spaced frames over a
time-aligned waveform, with silence gaps ≥0.35s shaded AND returned as data
(silences). The silence spans are your cut candidates before you have looked
at a single frame.
media_probefirst — duration, fps, resolution, has_audio.media_timelineover the whole clip for the first read; again over narrow ranges (±1.5s) at decision points — ambiguous pauses, boundary checks.media_frame+view_imageonly when you need one frame at full attention.- Audio is primary, visuals follow: cut candidates come from silence gaps and speech boundaries; drill into visuals only to confirm.
If a transcript helps (dialogue-heavy footage) and a speech-to-text workflow
is available, add a ComfyTV.SubtitleGenStage, run it, and read the SRT it
returns. Convert its cues to {text, start, end} objects and pass them as
words to media_timeline to get a labeled timeline. SRT cues are
phrase-level, not word-level — pad cuts more generously when relying on them.
Hard rules
- Strategy confirmation before execution. Describe the plan in plain English — what gets cut, kept, reordered, graded — and wait for the user's OK before building or running anything.
- Never cut mid-speech. Snap every cut edge to a silence gap from
media_timeline. Gaps ≥400ms are the cleanest; 150–400ms need a visual check; below 150ms is unsafe. - Pad every cut edge 30–200ms into the silence. Tighter for montage energy, looser for cinematic pacing.
- Subtitles burn LAST.
SubtitleStagegoes after every concat, speed, and FX stage in the chain — anything composited after it will cover the captions. - Preview cheap before rendering expensive. Iterate looks with
fx_preview(one FX stage, ~1.2s window) until the frame is right, THEN set the stage and render. Render one boundary clip to verify a doubtful cut before building the whole chain. - Self-eval before presenting. After the final render, run
media_timelineon the RENDERED output at every cut boundary (±1.5s): look for visual jumps, waveform spikes (audio pops), and captions hidden by later compositing. Fix and re-render at most 3 times, then flag what remains instead of looping. - Don't re-run what didn't change. Stages keep their outputs; Director clips re-render only when edited. Re-running an unchanged chain wastes the user's GPU time.
- The canvas is the project file. Keep the graph tidy (
arrange_canvas) and show the user what you built (canvas_focus). Never leave orphaned stages behind.
What ships with it
3 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.
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.
- 5d ago First seen · 135 lines · 111 tokens per session scan A 248a890f7e52
video-editor is a skill published in the GitHub repository jtydhr88/ComfyTV (967 stars, last pushed today), licensed MIT. It adds 111 tokens to every session and 1,731 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 2026-09-03.
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