agentic-video-understanding

name	Agentic video understanding
description	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 recordings. Goal-directed watch via Gemini agentic video understanding (frames, audio, or transcript). Not for cutting, overlays, rendering, scheduling, or publishing.

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

• Pre-call / sales-call mining: buyer objection, next step, competitive mention
• Shortform scoring: find a 3-second standalone hook and in/out points
• Longform / X research: named-person + contrast moments in podcast or YouTube tape
• Talent review: bar evidence in a Loom or trial recording
• Client audit: every mention of a keyword across a discovery recording

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

• No full fixed-FPS ingest when the agentic path is available
• No invented timestamps or quotes
• No dumping full transcripts or client PII into public artifacts
• No cut / render / overlay / schedule / publish / send from this skill

Setup

• Gemini API key or Google AI Studio access: https://ai.studio
• See Google’s developer guide for agentic video understanding in Gemini
• Env: GEMINI_API_KEY (or the project’s existing Google AI credential)

Caller one-liners

• Pre-call: goal="exact next-step commitment and any pricing pushback"
• Shortform: goal="best 3-second standalone hook; return in/out for one clip"
• Talent: goal="evidence they hit the role bar on X; max 5 moments"
• Audit: goal="every mention of Reddit, AEO, or budget"

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.