MarketingStrategy

Agentic video understanding

Use when an agent must extract moments, quotes, objections, hooks, or evidence from long video or audio cheaper than full-frame ingest — sales calls, podcasts, YouTube episodes, Loom trials, discovery…

EEric Siu·Marketing·MIT

Library skill — the default version is maintained in GitHub; edits you make live in your own clone.

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Agentic video understanding

Hireable understanding layer. The model takes a goal and decides what to watch, at what speed, and through which modality (frames, audio, transcript), fetching only the moments needed. Vendor claims: up to ~66% lower cost and ~88% fewer tokens vs static fixed-FPS ingest, with higher accuracy.

What this is / is not

Is: goal → watch only what you need → timestamps + quotes + confidence.

Is not: a video editor. Do not cut, overlay, caption-burn, render, schedule, post, email, or write CRM from this skill. Hand cuts to Overlap, FFmpeg, or net-new-video-editor. Approvals stay with the calling lane.

When to use

Skip when the job is already a clean transcript and you only need text search.

Inputs

Field Required Notes
source yes URL or local media path the runtime can read
goal yes One sentence retrieval goal
keywords no Extra strings to bias retrieval
max_moments no Default 5
modality no auto (default), frames, audio, or transcript

Process

  1. Restate the goal as 1–3 retrieval queries. Done when each query is falsifiable (you would know if a moment matched).
  2. Call Gemini agentic video understanding (Gemini API or AI Studio) with source, queries, max_moments, and modality preference. Prefer the agentic path over fixed-FPS full ingest when available. Done when the API returns candidate windows or an explicit empty set.
  3. Normalize moments into the output schema below. Flag paraphrase vs verbatim. Drop fabricated timestamps. Done when every kept moment has t_start, t_end, modality, quote, why, confidence.
  4. Stop and hand off to the caller. Do not cut, overlay, schedule, publish, email, or CRM-write.

Output schema

Markdown for humans, optional JSON for machines:

{
  "goal": "",
  "source": "",
  "moments": [
    {
      "t_start": "MM:SS",
      "t_end": "MM:SS",
      "modality": "frames|audio|transcript",
      "quote": "",
      "verbatim": true,
      "why": "",
      "confidence": 0.0
    }
  ],
  "empty_reason": null,
  "tokens_note": "agentic path used|fallback static ingest"
}

Hard gates

Setup

Caller one-liners

Completion

Done when the caller has the schema above (or a documented empty set) and this skill has performed no side effects beyond the Gemini read.