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get_moment

Read-onlyIdempotent

Capture a single moment's evidence in one call: transcript slice, up to 3 frames with OCR text, and the exact time range.

Instructions

The "one remark" evidence bundle: transcript slice + up to 3 unique frames + their OCR text + the wall-clock range for [start_ms, end_ms], in a single call. This is the workhorse for triage: one call per finding gives you the quote, the screenshot, and the on-screen text. When NOT to use: broad exploration (get_transcript / get_frames) or keyword lookup (search). Examples:

  • get_moment(job_id="...", start_ms=83000, end_ms=97000) — full evidence for the remark at 1:23-1:37

  • segment seq 12 spans t0_ms=83210, t1_ms=96800 → get_moment(job_id, 83210, 96800)

  • pad ±2000 ms around the spoken range — narrators react to things already on screen

  • triage loop: for each candidate finding, exactly one get_moment call → quote + frame + OCR

  • user: "what was I showing when I said 'this button is broken'?" → search first, then get_moment at the hit

  • opening context of a meeting: get_moment(job_id, 0, 15000)

  • response includes the t_wall range when known → quote it in bug reports for log correlation

  • diarized job → speakers_in_range + speaker on each segment: who is talking in this window, at a glance

  • frame entries carry "path" (absolute) — copy the screenshot elsewhere with your own file tools

  • "was X on screen at t?" → yes iff some frame's valid_from_ms <= t < valid_to_ms — no extra calls needed

  • audio-only job → returns the transcript slice plus a no-frames note (that is expected)

  • anti-example: whole-video summary → get_transcript(format="text"), not a chain of get_moments

  • anti-example: need more than 3 frames of a range → get_frames(start_ms=..., end_ms=..., max_frames=6)

  • keep ranges under ~30 s; a 5-min "moment" dilutes the bundle and wastes tokens

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_msYes
job_idYes
start_msYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Adds behavioral details beyond annotations: returns up to 3 frames, OCR, wall-clock range, audio-only handling, frame paths. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Very informative but lengthy. However, it is well-structured with clear sections and front-loaded key purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Complete for a tool with no output schema: covers return structure, edge cases (audio-only, diarized), and usage patterns.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema coverage, the description compensates fully, explaining start_ms/end_ms with examples, padding advice, and use cases.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Explicitly states it returns an evidence bundle with transcript slice, up to 3 frames, OCR, and time range. Distinguishes from siblings like get_transcript and search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when to use (one call per finding) and when not to use (broad exploration, keyword lookup). Includes multiple examples and anti-examples.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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