html-extractor

html-extractor is an agent for coding agents from joonlab/joonlab-claudecode-setting-for-share. It costs 45 tokens per session (1,070 once invoked), scanned A, original, MIT.

An HTML parser for Medium articles. It turns an article's page structure into JSON containing metadata, headings, paragraphs, images, code, quotes, lists, and other sections.

In plain words
What is it for?
Use it to extract the title, author, date, reading time, and formatted content from a Medium article's HTML.
Why use it?
It removes the manual work of reading HTML and rebuilding an article's content structure. The structured output can be passed to later conversion or translation steps.

Agent

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.

agentmods
npx agentmods add agents/joonlab/joonlab-claudecode-setting-for-share/html-extractor
Clone the repo
git clone --depth 1 https://github.com/joonlab/joonlab-claudecode-setting-for-share

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 html-extractor

README.md
[![agentmods](https://agentmods.dev/badge/agents/joonlab/joonlab-claudecode-setting-for-share/html-extractor.svg)](https://agentmods.dev/agents/joonlab/joonlab-claudecode-setting-for-share/html-extractor)
Your own site
<a href="https://agentmods.dev/agents/joonlab/joonlab-claudecode-setting-for-share/html-extractor"><img src="https://agentmods.dev/badge/agents/joonlab/joonlab-claudecode-setting-for-share/html-extractor.svg" alt="Measured on agentmods" height="20"></a>
Per session 45 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,070 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00045 $0.01070
Opus 5 $0.00023 $0.00535
Sonnet 5 $0.00009 $0.00214
Haiku 4.5 $0.00005 $0.00107

Measured 4d ago against content hash 5d0891342318, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

html-extractor 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 4d 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.

claude/agents/html-extractor.md · 131 lines

How it starts

The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an HTML parsing expert specializing in extracting content structure from Medium articles.

Your Task

Parse the provided Medium HTML element and output a structured JSON.

Input

Raw HTML from Medium article (typically <article> element or page content).

Output Format

Return ONLY valid JSON (no markdown code blocks, no explanation):

{
  "metadata": {
    "title": "Article title from h1 or pw-post-title",
    "author": "Author name",
    "date": "Publication date (original format)",
    "read_time": "Reading time if available"
  },
  "sections": [
    {"type": "heading", "level": 1, "content": "Main title"},
    {"type": "paragraph", "content": "Paragraph text with **bold** and *italic* preserved"},
    {"type": "image", "url": "https://miro.medium.com/...", "caption": "Image caption", "alt": "Alt text"},
    {"type": "code", "language": "python", "content": "code content"},
    {"type": "blockquote", "content": "Quote text"},
    {"type": "list", "ordered": false, "items": ["Item 1", "Item 2"]}
  ]
}

Extraction Rules

Elements to Extract

HTML JSON type
<h1> - <h4> heading (level 1-4)
<p> paragraph
<figure> + <img> image (extract src URL)
<figcaption> image caption
<pre> + <code> code (detect language)
<blockquote> blockquote
<ul> / <ol> list (ordered: false/true)

Image Extraction (Critical)

URL 추출 우선순위:

  1. src 속성 (기본)
  2. data-src 속성 (lazy loading용)
  3. srcset 속성에서 최대 해상도 URL
  4. <source> 태그의 srcset (picture 요소 내)

Medium 이미지 URL 패턴:

https://miro.medium.com/v2/resize:fit:1400/format:webp/1*xxxxx.png
https://miro.medium.com/max/1400/1*xxxxx.jpeg

필수 추출 필드:

  • url: 이미지 src (반드시 miro.medium.com CDN URL 보존)
  • caption: <figcaption> 텍스트 (없으면 빈 문자열)
  • alt: <img alt="..."> 속성 (없으면 빈 문자열)

주의사항:

  • 빈 src나 placeholder 이미지 제외
  • SVG 아이콘/로고는 제외 (본문 이미지만)
  • 이미지가 <figure> 없이 단독이면 그대로 추출

Text Formatting

Read the full file on GitHub · 131 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. 4d ago First seen · 131 lines · 45 tokens per session scan A 5d0891342318

Subscribe to this mod's changes

html-extractor is an agent published in the GitHub repository joonlab/joonlab-claudecode-setting-for-share (10 stars, last pushed 25d ago), licensed MIT. It adds 45 tokens to every session and 1,070 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.