| name | derive-thesis |
| description | Name the CENTRAL SUBJECT (spine) of a long-form source so selection can tell on-theme moments from clip-shaped tangents. Claude reads the topic chapter list (topics.json) + source duration and emits thesis.json = {subject, thesis_sentence, key_threads[]} — the one durable source-level "what is this video about" artifact the pipeline lacked. Runs AFTER segment-topics and BEFORE pick-segments; pick-segments feeds it as a theme prior + scores each pick's theme_fit against it, and the confidence-floor backfill is gated on it so a high-standalone but off-spine tangent can no longer be auto-injected. Deterministic fallback (subject from the longest topic) on any failure. Non-fatal, idempotent, DERIVE_THESIS=0 skips. |
| allowed-tools | Bash |
| user-invocable | true |
derive-thesis
A 2-hour talk wanders through one core throughline plus dozens of entertaining
tangents. Nothing in the pipeline named the throughline, so pick-segments
maximized standalone virality per span and shipped clip-shaped asides (a beetle
anecdote, a DoorDash story) that misrepresent the source. derive-thesis
computes that missing source-level subject once, as a durable JSON artifact both
pick-segments (theme prior + theme_fit score + backfill gate) and
selection-report read.
Invoke
.claude/skills/derive-thesis/derive-thesis.sh <transcript.json> [topics.json] [out.json]
transcript: full-source transcript (for duration; the digest is the topic list)topics: segment-topics output (auto-discovered next to the transcript)out: thesis.json (auto-discovered next to the transcript)
Output
thesis.json:
{
"subject": "Donald Hoffman on consciousness and reality",
"thesis_sentence": "Perception is a species-specific interface, not a window onto objective reality.",
"key_threads": ["conscious agents", "fitness beats truth", "spacetime is not fundamental", "the hard problem"]
}
On any Claude/parse failure it writes a deterministic fallback (subject from
the longest topic's title, key_threads from the leading topic titles,
"fallback": true) so downstream always has a subject.
How
build_prompt.py renders the whole chapter list and asks Claude to name the
SPINE (not summarize every chapter) — the guest + core theme, the throughline
sentence, and the on-spine sub-themes. parse_reply.py validates and clamps,
falling back to a topic-derived subject when the reply is empty/unparseable.
Idempotent via mtime (topics.json → thesis.json); DERIVE_THESIS=0 skips.
