agentleFS
saint0xsaint0x/my-skills/agent-watch/SKILL.md

agent-watch

Skill1 starsChanged 3 months agoMITView on GitHub

Watch a video or screen recording, ground answers in what was actually shown and said, and optionally distill the watch session into a new installed hyper-specific skill. Use when Codex needs to analyze a YouTube video, local `.mp4` or `.mov`, product demo, course lesson, bug repro recording, presentation, tutorial, cooking video, workflow walkthrough, or any visual process where transcript-only reasoning is insufficient and the resulting learning may need to become a reusable skill.

The file

Show its rules and text

We split this skill into the rules it gives an agent

18 rules. About 0 are common, 14 are distinctive, and 4 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈14

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use this skill when the model needs real video eyes and ears, not guesses from a title or transcript alone.

    line 8
  2. Distinctive:

    Keep the upstream watch runtime intact.

    line 10
  3. Distinctive:

    Run the bundled setup preflight before the first watch run.

    line 15
  4. Very specific:

    Run the bundled watch.py pipeline against the URL or local file.

    line 16
  5. Distinctive:

    If requested, distill the watch session into a new hyper-specific skill and install it locally.

    line 19
  6. Very specific:

    Treat the bundled scripts in scripts/ as the canonical runtime.

    line 23
  7. Distinctive:

    Prefer what was actually seen and heard over inferred summaries.

    line 24
  8. Distinctive:

    Use focused re-runs for specific moments instead of sparse whole-video rescans.

    line 25
  9. Distinctive:

    Do not create a learned skill from vague inspiration alone.

    line 26
  10. Distinctive:

    Only create a learned skill when the video yields a repeatable, operational pattern that would help future work.

    line 27
  11. Distinctive:

    When creating a learned skill, make it specific to the observed method, style, sequence, tools, constraints, cues, and failure modes from …

    line 28
  12. Distinctive:

    Do not genericize the learned skill into broad internet advice unless the user explicitly asks for abstraction.

    line 29
  13. Distinctive:

    Read references/watch-operations.md before substantial use.

    line 33
  14. Distinctive:

    When the user wants the watch session converted into a reusable skill, read references/skill-distillation.md and follow it strictly.

    line 45
  15. Very specific:

    create a new skill scaffold with scripts/init_learned_skill.py

    line 49
  16. Distinctive:

    write the new skill in the repo or install root the user wants

    line 50
  17. Very specific:

    Use scripts/init_learned_skill.py when you need a fast local scaffold for a new learned skill.

    line 57
  18. Distinctive:

    Read these only as needed:

    line 67

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Agent Watch

Use this skill when the model needs real video eyes and ears, not guesses from a title or transcript alone.

Keep the upstream watch runtime intact. Extend it by turning durable lessons from a watch session into a new local skill only when the user wants that outcome.

Core Workflow

  1. Resolve the absolute path of this skill directory.
  2. Run the bundled setup preflight before the first watch run.
  3. Run the bundled watch.py pipeline against the URL or local file.
  4. Inspect the returned frames and transcript together.
  5. Answer the user from observed evidence, with timestamps when helpful.
  6. If requested, distill the watch session into a new hyper-specific skill and install it locally.

Working Rules

  • Treat the bundled scripts in scripts/ as the canonical runtime.
  • Prefer what was actually seen and heard over inferred summaries.
  • Use focused re-runs for specific moments instead of sparse whole-video rescans.
  • Do not create a learned skill from vague inspiration alone.
  • Only create a learned skill when the video yields a repeatable, operational pattern that would help future work.
  • When creating a learned skill, make it specific to the observed method, style, sequence, tools, constraints, cues, and failure modes from that source.
  • Do not genericize the learned skill into broad internet advice unless the user explicitly asks for abstraction.

Setup and Execution

Read references/watch-operations.md before substantial use.

Use it for:

  • setup and preflight flow
  • detail modes and token tradeoffs
  • focused-window re-runs
  • transcript-cue frames
  • failure handling

Distilling a Learned Skill

When the user wants the watch session converted into a reusable skill, read references/skill-distillation.md and follow it strictly.

Default behavior:

  • create a new skill scaffold with scripts/init_learned_skill.py
  • write the new skill in the repo or install root the user wants
  • include only knowledge actually learned from the watched source
  • make the skill narrow, operational, and non-generic
  • install it locally after writing it

Bundled Helper

Use scripts/init_learned_skill.py when you need a fast local scaffold for a new learned skill. It creates:

  • SKILL.md
  • agents/openai.yaml
  • references/source-notes.md

Then replace the scaffold text with the actual learned procedure from the watch session.

Read Next

Read these only as needed:

  • references/watch-operations.md
  • references/skill-distillation.md

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