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.
npx skills add 0-bingwu-0/html-knowledge-base-templates --skill digestgit clone --depth 1 https://github.com/0-bingwu-0/html-knowledge-base-templatesWrote 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.
[](https://agentmods.dev/skills/0-bingwu-0/html-knowledge-base-templates/digest)<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>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.
| Model | Per session | Once 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 |
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.
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 formatYYYY-MM-DD. Verify from the video / podcast page if not explicitly given.- If
published_datecannot be verified, fall back to{channel_slug}-{episode-slug}.htmlusing 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.
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.
- 7d ago First seen · 208 lines · 38 tokens per session scan A f5635f323dbe
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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