Jiang Source Ingest

Use this for the mechanical path from committed raw source artifacts into canonical source state.

This skill does not write public episode prose, public lens docs, glossary canon, or promotion records.

Core Rule

Treat time as part of provenance. A claim is not just "what Jiang says"; it is what a dated artifact records him saying, in a specific context, with a stable source ref.

Inputs

Committed Colab text artifacts:

content/sources/raw/youtube/<channel>/<video-id>/
  metadata.youtube.json
  dump.json
  grouped.json
  transcription.json

content/sources/raw/youtube/Interviews/<host-channel-id>/<video-id>/
  metadata.youtube.json
  dump.json
  grouped.json
  transcription.json

If artifacts are still only in Google Drive or Colab, use colab-video-pipeline first, then commit the synced text artifacts. ops/staging/ is only a local disposable cache, not the worker source of truth.

Import Flow

First check the source-processing policy:

content/workflow/tasks/source-processing-policy.json

If the video ID is marked duplicate, blocked, skip, or archive-only, do not import it as a new source. The raw folder remains useful archive evidence, but it should not create a second episode, second transcript source, or second downstream corpus-impact obligation. Use --force-policy only when the maintainer explicitly overrides the policy.

Import:

node ops/scripts/import-colab-video.mjs \
  --video-id VIDEO_ID \
  --channel @PredictiveHistory

# for interview-format sources
node ops/scripts/import-colab-video.mjs \
  --video-id VIDEO_ID \
  --channel Interviews/<host-channel-id>

Inspect:

node ops/scripts/inspect-source.mjs \
  content/sources/videos/<source-slug>

Prepare packets:

node ops/scripts/prepare-agent-transcript-packets.mjs \
  --source content/sources/videos/<source-slug>

The E2E integration script can run these steps for one video:

node ops/scripts/process-video-e2e.mjs --video-id VIDEO_ID --channel @PredictiveHistory
# or, for interview-format sources:
node ops/scripts/process-video-e2e.mjs --video-id VIDEO_ID --channel Interviews/<host-channel-id>

Outputs

content/sources/videos/<source-slug>/metadata.json
content/sources/videos/<source-slug>/transcripts/v1/transcript.clean.jsonl
content/sources/videos/<source-slug>/transcripts/v1/transcript.clean.md
content/workflow/tasks/<source-slug>/transcript-agent-packets.jsonl

Do not commit raw audio or video.

Chronology Fields

Each source should include:

• source_class: episode for Predictive History lectures, interview for interview-format appearances.
• collection: episodes or interviews; this controls the public route generated by the compiler.
• recorded_at: when the statement was made, if known.
• published_at: when the artifact became public.
• date_precision: day, month, year, or unknown.
• chronology_status: dated or needs-date.

Prefer recorded_at when reasoning about what Jiang believed at a time. Use published_at when recorded_at is unknown, but label precision honestly.

The importer reads raw metadata.youtube.json when present. If it is missing, it may try yt-dlp by video ID, cache compact metadata into the raw source artifact folder, and use published_at for chronology.

Transcript Timing

When transcription.json includes turns[].words[], preserve phrase-level timed_chunks inside each clean segment. The transcript page uses those chunks for speech-following highlights.

After import, verify when needed:

node -e "const fs=require('fs');const lines=fs.readFileSync('content/sources/videos/<source-slug>/transcripts/v1/transcript.clean.jsonl','utf8').trim().split('\n').map(JSON.parse);console.log(lines.reduce((s,x)=>s+(x.timed_chunks?.length||0),0))"

If this prints 0, the transcript can still highlight whole segments, but not phrase-by-phrase. Do not fake phrase timing in the website layer.

Source Refs

Use stable refs:

video:<source-slug>@transcript:v1#seg-0001

The importer owns segment IDs and transcript text. It does not decide what is a real interaction, claim, model, glossary item, or public episode argument. Those belong to later skills.

Boundary

After ingest, hand off to:

• jiang-transcript-boundary-review if boundary candidates require decisions,
• jiang-agent-transcript-pass for semantic packet outputs,
• jiang-episode-read-writer only after semantic bundle and transcript are ready,
• jiang-canon-promotion only after proposal and review records exist.