watch

watch is a skill for Claude Code, Codex from gooseworks-ai/goose-skills. It costs 36 tokens per session (954 once invoked), scanned A, original, MIT.

A video review tool that watches a rendered file and reports what appears on screen and in its audio at specific times. It can inspect visuals, spoken audio, music, and sound effects.

In plain words
What is it for?
Use it to review an entire video or selected time ranges, check spoken content and audio layers, and create an observation report.
Why use it?
It gives you a timestamped account of what the finished video actually contains before you decide whether anything needs changing.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to review an entire video or selected time ranges, check spoken content and audio layers, and create an observation report.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/gooseworks-ai/goose-skills/watch
About the project

Goose Skills is a library of workflows and data APIs that lets coding agents handle growth and go-to-market work such as advertising, social media, content, SEO, lead generation, and customer research. It is intended for teams using Claude Code, Cursor, Codex, and similar agents. The catalogue entries are its reusable skills.

gooseworks-ai/goose-skills · 1,202 stars · on GitHub · gooseworks.ai

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 gooseworks-ai/goose-skills --skill watch
Clone the repo
git clone --depth 1 https://github.com/gooseworks-ai/goose-skills

Made for: Claude Code, Codex.

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 watch

README.md
[![agentmods](https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/watch/github.svg)](https://agentmods.dev/skills/gooseworks-ai/goose-skills/watch)
Your own site
<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/watch"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/watch/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 watch

Your own site · 80×15
<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/watch"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/watch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 954 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 pass 7 Sept 2026
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 $0.00036 $0.00954
Opus 5 $0.00018 $0.00477
Sonnet 5 $0.00007 $0.00191
Haiku 4.5 $0.00004 $0.00095

Measured 8d ago against content hash b8de719e55f5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

watch 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 8d 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.

skills/ads/packs/video-ad-formats/watch/SKILL.md · 64 lines

How it starts

The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.

watch

Purpose

Look at a rendered video and report what is actually on screen and in the audio. By default it watches the entire video and considers visuals, voiceover, music, and sound effects. Callers can narrow the scope (specific timestamp ranges, lower frame rate, disable audio tracks) when they want a cheaper or more focused pass.

This is the observation primitive that watch-and-refine calls before deciding what to fix. Other review and editing skills can call it directly.

Inputs

  • video — path to a local video file. Required.
  • ranges — optional list of [start, end] timestamps to watch. Accepts SS, MM:SS, or HH:MM:SS. Defaults to the whole video.
  • fps — frame sampling rate. Defaults to auto by duration (≤30s → 1–2 fps, 30s–1min → ~1 fps, 1–3min → ~0.5 fps, 3–10min → ~0.25 fps). Hard cap 2 fps.
  • max_frames — hard cap on total frames sampled across all ranges. Default 100.
  • resolution — frame width in px. Default 512. Bump to 1024 only when on-screen text legibility matters.
  • include_voice — bool, default true. Transcribe spoken VO/dialogue.
  • include_music — bool, default true. Describe music presence, swells, drops, gain relative to VO.
  • include_sfx — bool, default true. Note sound effects, foley, transition stingers.
  • focus — optional free-text prompt describing what to pay attention to (e.g. "watch the end card", "judge cut timing on the beat drop").

If all three audio flags are false, the skill runs frames-only and notes this in the manifest.

Workflow

  1. Validate video exists and is readable. Probe duration with ffprobe.
  2. Resolve ranges: if empty, use [0, duration]. Reject ranges outside the file duration.
  3. Resolve fps: use caller value if provided, else auto-scale from total resolved range duration. Clamp at 2 fps.
  4. Allocate the max_frames budget across ranges proportionally to range duration.
  5. Extract frames with ffmpeg into frames/ at the resolved fps and resolution.
  6. If any audio flag is true, extract the audio for the resolved ranges to a working WAV. Run a transcript pass when include_voice=true; degrade to frames-only and flag a warning if no Whisper backend is available.
  7. Compose observation.md — a timestamp-keyed report. Each entry references the frame paths visible during that window plus any transcript line and audio notes (music/SFX) for the same window. If focus is set, lead each entry with what was observed about that focus.
  8. Write manifest.json capturing the resolved inputs (ranges, fps, frame count, audio flags) and output paths.

Read the full file on GitHub · 64 lines

Files

What ships with it

7 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. 8d ago First seen · 64 lines · 36 tokens per session scan A b8de719e55f5

Subscribe to this mod's changes

watch is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 36 tokens to every session and 954 once invoked, about $0.0002 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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