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Agent skill

Watch

by gooseworks-ai in gooseworks-ai/goose-skills

Watch a rendered video (whole file or specific ranges) at a chosen fidelity and emit a timestamp-keyed observation report.

MITAuto-check passedMedia & Creative

Install Watch

skills CLI
$ npx skills add gooseworks-ai/goose-skills --skill watch -a claude-code

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

GitHub CLI
$ gh skill install gooseworks-ai/goose-skills watch --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/gooseworks-ai/goose-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ads/packs/video-ad-formats/watch .claude/skills/watch && 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
watch
GitHub stars
1.2k
Used in
1 other repo
Token cost
~1.1k tokens
SKILL.md length
584 words
Files
8 (incl. references)
Skills in repo
273
Repo updated
First seen
Licence
MIT

At a glance

Watch a rendered video (whole file or specific ranges) at a chosen fidelity and emit a timestamp-keyed observation report.

  • Works in 8 steps: Validate video exists and is readable.… → Resolve ranges: if empty, use [0,… → Resolve fps: use caller value if… → …
  • Media & Creative work in your project
  • SKILL.md covers Purpose, Inputs, Workflow and Output, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Watch is an agent skill from gooseworks-ai/goose-skills. Watch a rendered video (whole file or specific ranges) at a chosen fidelity and emit a timestamp-keyed observation report. Observation only — no edits, no verdicts.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `references/parameters.md`, `skill.meta.json` and `tests/expected-output.md`).

It sits in Media & Creative. The repository describes itself as: Library of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping. The licence is MIT.

When your agent uses it

  • Media & Creative work in your project

Example prompts

  • “/watch”

Workflow steps

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

  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…
  7. Compose observation.md — a timestamp-keyed report. Each entry references the frame paths visible during that window plus any transcript…
  8. Write manifest.json capturing the resolved inputs (ranges, fps, frame count, audio flags) and output paths.

What it can do on your machine

Read from SKILL.md and the folder at commit c650c6d. 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

    No scripts in the folder and no shell commands in SKILL.md.

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

  • Network

    No URLs in SKILL.md.

    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

Watch loads about 1.1k tokens when it runs, and up to ~1.6k if it reads all its reference files. Until then it costs about 43 tokens; SKILL.md has 584 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~43
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.6k

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 gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 584 words, ~1,058 tokens.

Download SKILL.mdSave it as .claude/skills/watch/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
watch
description
Watch a rendered video (whole file or specific ranges) at a chosen fidelity and emit a timestamp-keyed observation report. Observation only — no edits, no verdicts.

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.

Watch every assembled generated video at up to 2 fps. Real-time playback smooths over what frames show plainly: a half-second face flash, a wardrobe pop at a cut, a frozen scene, an invented background element.

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.
Show full SKILL.md (157 more words)Show less

Output

  • observation.md — timestamp-keyed observation report. No verdicts, no "good/bad" framing.
  • frames/*.jpg — sampled frames referenced from the report.
  • transcript.json — word-timestamped transcript, only when include_voice=true and a Whisper backend was available.
  • manifest.json — resolved inputs and output paths.

Quality Checks

  • Frame count never exceeds max_frames.
  • Every range produced at least one frame, unless the range is shorter than 1 / fps.
  • When include_voice=true, the transcript covers the resolved ranges (no >500ms gap inside a VO segment unless the audio itself is silent there).
  • All paths in manifest.json resolve to real files.
  • The report contains no recommendations — it describes only what was observed.

Failure Modes

  • Missing or unreadable video.
  • A ranges entry falls outside the file duration.
  • include_voice=true but no Whisper backend is configured — degrade to frames-only and flag a warning in the manifest.
  • max_frames budget too tight to give every range at least one frame — surface which ranges were skipped.

References

  • references/parameters.md — full parameter reference, defaults, and the auto-fps budget table.

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

Files

SKILL.md and 7 other files (references) in skills/ads/packs/video-ad-formats/watch of gooseworks-ai/goose-skills.

  • SKILL.md
  • references/parameters.md
  • skill.meta.json
  • tests/expected-output.md
  • tests/human-test.md
  • tests/sample-input.md
  • tests/smoke-test.md
  • tests/verifier.md

Open the folder on GitHubat commit c650c6d

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in gooseworks-ai/goose-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Watch 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.

Watch compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Watch this skillgooseworks-ai/goose-skills1.2k1 repos~1.1kAutomated safety check: PassMIT
Guizang Social Cardsop7418/guizang-social-card-skill7.4k1 repos~7.8kAutomated safety check: PassAGPL-3.0
Weekly Changelog Videoheygen-com/hyperframes60k—~3.3kAutomated safety check: PassApache-2.0
Anthropic Brand Stylinganthropics/skills180k30 repos~559Automated safety check: PassApache-2.0
MoneyPrinterTurbo Video Generatorharry0703/MoneyPrinterTurbo130k—~2.1kAutomated safety check: WarnMIT
HyperFrames Media Useheygen-com/hyperframes60k—~2.4kAutomated safety check: PassApache-2.0

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Categories

Questions about Watch

What does Watch do?

Watch a rendered video (whole file or specific ranges) at a chosen fidelity and emit a timestamp-keyed observation report. Watch is an agent skill from gooseworks-ai/goose-skills. Watch a rendered video (whole file or specific ranges) at a chosen fidelity and emit a timestamp-keyed observation report.

When should I use Watch?

Watch fits situations like: media & Creative work in your project.

How do I install Watch in Claude Code?

Run `npx skills add gooseworks-ai/goose-skills --skill watch -a claude-code`. Or copy the skill folder (skills/ads/packs/video-ad-formats/watch in gooseworks-ai/goose-skills) into .claude/skills/watch in your project. Claude Code loads it when a task matches its description.

How do I install Watch in Codex?

Run `npx skills add gooseworks-ai/goose-skills --skill watch -a codex`. Or copy the skill folder (skills/ads/packs/video-ad-formats/watch in gooseworks-ai/goose-skills) into .agents/skills/watch in your project. Codex loads it when a task matches its description.

Can I use Watch 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 gooseworks-ai/goose-skills --skill watch -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/watch, .gemini/skills/watch, .github/skills/watch and .opencode/skills/watch in your project.

What does Watch need to run?

SKILL.md names no scripts, command-line tools or credentials: Watch is instructions for the agent only.

Does Watch access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Watch 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 Watch use?

Watch 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 Watch use?

About 1.1k tokens (SKILL.md is roughly 4.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 511 tokens, read only when the agent opens those files.

What are the alternatives to Watch?

Skills that share tags, products or a category with Watch: Guizang Social Cards (op7418/guizang-social-card-skill, 7.4k stars), Weekly Changelog Video (heygen-com/hyperframes, 60k stars), Anthropic Brand Styling (anthropics/skills, 180k stars) and MoneyPrinterTurbo Video Generator (harry0703/MoneyPrinterTurbo, 130k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Watch?

gooseworks-ai (a GitHub organization) maintains it in gooseworks-ai/goose-skills, which has 1,240 GitHub stars. The repository holds 273 skills in this directory. The repository was last updated on October 8, 2026.

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