pick-segments

Claude-driven segment selection. No heuristics — Claude judges what's clip-worthy.

Inputs

• transcript: path to transcribe output JSON
• audio_rms (optional): path to a per-second RMS energy JSON (computed inline if missing)
• topics (optional): path to a segment-topics output JSON. Auto-discovered as topics.json next to the transcript. When present, topics act as a MAP of where ideas live, not a fence: a SINGLE-cut span that straddles a topic boundary is dropped (a raw slice crossing a chapter is two half-ideas), but a MULTI-cut span may pull cuts from different topics when every cut develops the same one idea (named in idea). ASSEMBLE_CROSS_TOPIC=0 restores the old hard constraint (cross-topic requires thread:true).
• heatmap (auto-discovered): YouTube most-replayed data from ingest. This is a weak discovery hint and tie-breaker, not a selection mandate.
• n: number of shorts to pick, default 5
• duration (optional): target duration range, default [20, 60] seconds
• out (optional): output JSON path

Output

{
  "shorts": [
    {
      "t0": 124.8,
      "t1": 156.3,
      "cuts": [[124.8, 156.3]],
      "idea": "Why the bit only lands after the audience turns on him.",
      "rationale": "Strong reaction shot followed by punchline — laughter at 152s.",
      "title_suggestion": "When the bit finally lands",
      "hook_score": 8,
      "context_score": 9,
      "structure_score": 8,
      "overall_score": 8.5,
      "replay_quotient": 1.2
    },
    ...
  ]
}

How

1. Compute audio RMS at 1Hz from the source video (ffmpeg → wave → numpy) if not provided.
2. Build a compact context: transcript text with timestamps every line, RMS energy summary, optional replay heatmap, and topic boundaries.
3. Ask Claude for complete standalone story arcs — single-idea assemblies whose cuts may come from anywhere in the source. The hierarchy is cold-viewer context first, the 1s SPOKEN hook second (assume NO title card / on-screen text), replay/RMS only as supporting evidence.
4. Validate ranges (non-overlap, duration bounds, single-cut topic containment, filler openings, spoken-hook floor), add a small replay tie-breaker, write JSON.

Knobs (shorts-sgpa)

• ASSEMBLE_CROSS_TOPIC (default 1): 0 = exact rollback — a multi-cut cross-topic span requires thread:true again.
• PICK_HOOK_FLOOR (default 5.0): picks with hook_score below this are dropped; never empties the set (keeps the single best-hook pick + WARN). 0 disables.
• PAYOFF_BUDGET_SEC (default 2.0, was 3.0): the turn must land ~2s into the delivered open; later payoffs take a ~2.2 pts/s rank penalty.

For batch / large transcripts, a /crew member can be spawned to keep this off the host session.

ADVICE_CORPUS toggle (experimental, default OFF — epic shorts-dwt)

ADVICE_CORPUS=1 prepends the versioned §9 entertainment-advice corpus (advice.md) to the picker prompt; unset/0 emits today's prompt byte-for-byte. The corpus lives in its own file so it is A/B-able independently of code. Whether it actually improves clip SELECTION is being measured non-circularly (no Claude in the scorer) per tools/eval/PRE-REGISTRATION.md; it ships as default only after a CI-clean Tier-2 win. The invariant "OFF = verbatim, ON = OFF + corpus and nothing else" is locked by test_advice_toggle.py. (Later extend the same gate to rlm-segment-subcall.)

Status

Stub. Implementation: bd ready.