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Run npx skillmds@latest add simonlee2/video-digest-summarize in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Is Video Digest Summarize free to use?

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Who published Video Digest Summarize?

simonlee2 (@simonlee2) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Video Digest Summarize by simonlee2

Name: Video Digest Summarize
Author: simonlee2

Video Digest Summarize

Turn segmented talk transcripts into digest text - per-talk transcript slices, cleaned transcripts, summary docs with timestamped highlights, TL;DR + practical takeaway JSON, and optional Traditional Chinese translation. Stage 3 of the video-digest pipeline, after ingest (and segment for multi-talk streams). Use when summarizing talks for a video digest.

simonlee2 6005943 6 files · 11.0 KB Updated Sep 17, 2026

File contents

video-digest-summarize

Input: <item_dir> with talks.json + transcript/transcript.tsv. See video-digest for layout/config.

1. Deterministic prep (scripts/)

python3 scripts/vd_sessions.py <item_dir> [--clips]   # slices + manifest.json (+ per-talk clips)
python3 scripts/vd_clean.py <item_dir>                # cleaned transcript, glossary from digest.json

vd_sessions.py: per talk sessions/NN_slug.txt ("[HH:MM:SS] text" lines, video offsets) + manifest.json. --clips also cuts lossless per-talk mp4s (only useful for multi-talk streams; skipped automatically when a talk spans the whole video).
vd_clean.py: collapses Whisper loop/applause runs, applies glossary/nonspeech from the project's digest.json (walks up from item_dir) → transcript/transcript.clean.txt, sessions/*.clean.txt, transcript/corrections.md.

2. LLM steps (prompts in `references/`; fan out ~5 talks per agent)

Prompt	Reads	Writes
`summarize-prompt.md`	`sessions/<name>.txt`	`sessions/<name>.md` (Summary, timestamped Highlights, quotes)
`takeaway-prompt.md`	`sessions/<name>.md`	`sessions/<name>.take.json` `{"tldr","takeaway"}`
`translate-prompt.md`	highlights.json + take.json	`zh.json` — only if project `languages` includes `"zh"`; run AFTER the slides stage (needs highlights.json)

Fill {ITEM_DIR} and {AUDIENCE} (from digest.json audience) in prompts.

Order note

summarize → takeaway can run right after this stage's scripts; the slides stage then extracts frames at each highlight timestamp. Translation last (it reads highlights.json from the slides stage).

Glossary loop

After the pilot item, read transcript/corrections.md + skim a sessions/*.md for recurring ASR errors (product names, speaker names) → add regex pairs to digest.json.glossary, re-run vd_clean.py. Only unambiguous fixes; never risky common-word swaps.

---name: video-digest-summarizedescription: Turn segmented talk transcripts into digest text - per-talk transcript slices, cleaned transcripts, summary docs with timestamped highlights, TL;DR + practical takeaway JSON, and optional Traditional Chinese translation. Stage 3 of the video-digest pipeline, after ingest (and segment for multi-talk streams). Use when summarizing talks for a video digest.---# video-digest-summarizeInput: `<item_dir>` with `talks.json` + `transcript/transcript.tsv`. See `video-digest` for layout/config.## 1. Deterministic prep (scripts/)```python3 scripts/vd_sessions.py <item_dir> [--clips] # slices + manifest.json (+ per-talk clips)python3 scripts/vd_clean.py <item_dir> # cleaned transcript, glossary from digest.json```- `vd_sessions.py`: per talk `sessions/NN_slug.txt` ("[HH:MM:SS] text" lines, video offsets) + `manifest.json`. `--clips` also cuts lossless per-talk mp4s (only useful for multi-talk streams; skipped automatically when a talk spans the whole video).- `vd_clean.py`: collapses Whisper loop/applause runs, applies `glossary`/`nonspeech` from the project's `digest.json` (walks up from item_dir) → `transcript/transcript.clean.txt`, `sessions/*.clean.txt`, `transcript/corrections.md`.## 2. LLM steps (prompts in `references/`; fan out ~5 talks per agent)| Prompt | Reads | Writes ||---|---|---|| `summarize-prompt.md` | `sessions/<name>.txt` | `sessions/<name>.md` (Summary, timestamped Highlights, quotes) || `takeaway-prompt.md` | `sessions/<name>.md` | `sessions/<name>.take.json` `{"tldr","takeaway"}` || `translate-prompt.md` | highlights.json + take.json | `zh.json` — only if project `languages` includes `"zh"`; run AFTER the slides stage (needs highlights.json) |Fill `{ITEM_DIR}` and `{AUDIENCE}` (from digest.json `audience`) in prompts.## Order notesummarize → takeaway can run right after this stage's scripts; the slides stage then extracts frames at each highlight timestamp. Translation last (it reads highlights.json from the slides stage).## Glossary loopAfter the pilot item, read `transcript/corrections.md` + skim a `sessions/*.md` for recurring ASR errors (product names, speaker names) → add regex pairs to `digest.json.glossary`, re-run `vd_clean.py`. Only unambiguous fixes; never risky common-word swaps.

Frequently asked questions