digest

digest is a skill for Claude Code, Codex from 0-bingwu-0/html-knowledge-base-templates. It costs 38 tokens per session (1,473 once invoked), scanned A, original, MIT.

A transcript-to-notes workflow for YouTube videos and podcasts. It turns a full transcript into question-and-answer knowledge cards with expandable supporting evidence in an existing HTML template.

In plain words
What is it for?
Use it to read transcripts from podcast/transcripts, extract standalone Q&A cards, and render the result into podcast/notes as an HTML file.
Why use it?
It makes long conversations easier to scan without losing the transcript passages behind each answer. It also applies consistent input names, output names, and formatting.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to read transcripts from podcast/transcripts, extract standalone Q&A cards, and render the result into podcast/notes as an HTML file.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/0-bingwu-0/html-knowledge-base-templates/digest
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add 0-bingwu-0/html-knowledge-base-templates --skill digest
Clone the repo
git clone --depth 1 https://github.com/0-bingwu-0/html-knowledge-base-templates

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for digest

README.md
[![agentmods](https://agentmods.dev/badge/skills/0-bingwu-0/html-knowledge-base-templates/digest.svg)](https://agentmods.dev/skills/0-bingwu-0/html-knowledge-base-templates/digest)
Your own site
<a href="https://agentmods.dev/skills/0-bingwu-0/html-knowledge-base-templates/digest"><img src="https://agentmods.dev/badge/skills/0-bingwu-0/html-knowledge-base-templates/digest.svg" alt="Measured on agentmods" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,473 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00038 $0.01473
Opus 5 $0.00019 $0.00737
Sonnet 5 $0.00008 $0.00295
Haiku 4.5 $0.00004 $0.00147

Measured 7d ago against content hash f5635f323dbe, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

digest scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

podcast-question-cards/skills/digest/SKILL.md · 208 lines

How it starts

The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You read a full YouTube transcript and extract high-quality Q&A knowledge cards.

Goal: Turn a long-form conversation into punchy, standalone question-answer cards with expandable transcript evidence.

Use the HTML template in:

template/index.html

Do not invent a new layout. Only replace placeholders and repeat the QA card block.


INPUT FILE

Read the transcript from:

podcast/transcripts/{channel_slug}-{published_date}.md

Example: podcast/transcripts/lenny-2026-05-03.md


OUTPUT FILE

Write the rendered HTML to:

podcast/notes/{channel_slug}-{published_date}.html

Rules:

  • channel_slug: short lowercased slug of the source/channel name (e.g. "Lenny's Podcast" → lenny, "How I AI" → how-i-ai). Strip apostrophes, replace spaces with hyphens, drop punctuation. Prefer a short recognizable form over the full channel name.
  • published_date: ISO format YYYY-MM-DD. Verify from the video / podcast page if not explicitly given.
  • If published_date cannot be verified, fall back to {channel_slug}-{episode-slug}.html using a short hyphenated slug of the episode title.

Example: podcast/notes/lenny-2026-05-03.html

Do NOT paste HTML into chat. The chat response should only say:

Created podcast/notes/{filename}


INPUT

The input may include:

  • episode title
  • source / show name
  • guest name and role
  • published date
  • original URL
  • full transcript

Use metadata exactly as provided. Do not invent missing metadata. If a metadata field is missing, omit that entirely from the episode-meta list.


METADATA CORRECTNESS

Before writing the HTML, sanity-check metadata against the original source:

  • Episode title: use the exact original title from the video / podcast page. Do not paraphrase, rewrite, translate, or "improve" it. If the URL is provided, fetch/search to confirm the canonical title.
  • Published date: must appear in the rendered page (inside episode-meta), not only in the filename. Verify from the video / podcast page if not explicitly given. Render it in a readable form consistent with the page's language (e.g. "May 3, 2026" for English pages, "2026 年 5 月 3 日" for Chinese pages).
  • Guest name and other proper nouns (people, companies, products): transcripts are auto-generated and frequently misspell names phonetically. Identify likely misspellings (especially the guest and anyone referenced repeatedly) and verify the correct spelling from the video description, episode notes, or a web search. Apply corrections consistently across both metadata and every source passage.

If you cannot verify a name with reasonable confidence, keep the transcript spelling and do not guess.


CARD SELECTION

Extract only topics that are:

  • substantively discussed
  • concretely tied to real companies, technologies, industries, policies, products, markets, roles, or social changes
  • understandable without watching the episode
  • still interesting after the episode is forgotten

Prefer fewer strong cards over many weak ones.

Skip:

  • filler
  • biography
  • generic life advice
  • one-off tangents
  • vague trend talk
  • repeated points
  • shallow summaries

Merge duplicate kernels across the episode. Keep the clearest version with the richest supporting exchange.


QUESTION RULES

Each question should:

  • be 8–18 words
  • be one sentence
  • end with "?"
  • feel like a debate prompt or strong headline
  • create a real contested answer space

Avoid:

  • vague essay prompts
  • "A or B?" framing
  • smuggled assumptions
  • jargon-only wording

ANSWER RULES

Write ONE sharp declarative sentence.

Rules:

  • 10–25 words
  • no hedging
  • no "the speaker argues"
  • no balance framing
  • concrete and opinionated
  • faithfully reflect the video's stance

SOURCE PASSAGE

Each card must include the FULL supporting transcript exchange.

Start where the topic is introduced. End when the conversation meaningfully moves on.

Include:

  • host questions
  • guest answers
  • back-and-forth
  • clarifications
  • disagreements

Do not paraphrase transcript text. Err on the side of MORE context.

Read the full file on GitHub · 208 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 208 lines · 38 tokens per session scan A f5635f323dbe

Subscribe to this mod's changes

digest is a skill published in the GitHub repository 0-bingwu-0/html-knowledge-base-templates (5 stars, last pushed 3mo ago), licensed MIT. It adds 38 tokens to every session and 1,473 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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