multi-agent-browser-text-extraction

multi-agent-browser-text-extraction is a skill for Claude Code, Codex from ChrisLamDev/hermes-core-skills. It costs 51 tokens per session (1,175 once invoked), scanned A, original, MIT.

A method for using several browser-equipped agents to copy exact text from Chinese academic or religious websites whose navigation depends heavily on JavaScript. JavaScript is code that makes web pages interactive.

In plain words
What is it for?
Use it to collect ten or more pages of verbatim text from chapter-based sites, including sites with tree menus, bot detection, or content loaded after clicks.
Why use it?
These sites can hide content behind expandable menus, load pages dynamically, or react differently to automated visitors. Parallel agents help extract many chapters and verify the results.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents; mentions Codex.

Good fit Use it to collect ten or more pages of verbatim text from…

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Install with agentmods
npx agentmods add skills/chrislamdev/hermes-core-skills/multi-agent-browser-text-extraction
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 ChrisLamDev/hermes-core-skills --skill multi-agent-browser-text-extraction
Clone the repo
git clone --depth 1 https://github.com/ChrisLamDev/hermes-core-skills

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 multi-agent-browser-text-extraction

README.md
[![agentmods](https://agentmods.dev/badge/skills/chrislamdev/hermes-core-skills/multi-agent-browser-text-extraction.svg)](https://agentmods.dev/skills/chrislamdev/hermes-core-skills/multi-agent-browser-text-extraction)
Your own site
<a href="https://agentmods.dev/skills/chrislamdev/hermes-core-skills/multi-agent-browser-text-extraction"><img src="https://agentmods.dev/badge/skills/chrislamdev/hermes-core-skills/multi-agent-browser-text-extraction.svg" alt="Measured on agentmods" height="20"></a>
Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,175 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 $0.00051 $0.01175
Opus 5 $0.00026 $0.00588
Sonnet 5 $0.00010 $0.00235
Haiku 4.5 $0.00005 $0.00118

Measured 7d ago against content hash acd5dd1ef435, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

multi-agent-browser-text-extraction 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.

skills/multi-agent-browser-text-extraction/SKILL.md · 118 lines

How it starts

The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Multi-Agent Browser Text Extraction

Extract large volumes of original text from JavaScript-heavy Chinese websites (e.g. ddc.shengyen.org 法鼓全集) using parallel delegate_task sub-agents, each with browser toolset.

When to Use

  • Target site has JS-heavy tree menu navigation (not static HTML)
  • Need to extract 10+ pages of verbatim text from different chapters/books
  • Site has bot detection that varies by URL path
  • Each extraction requires clicking through tree menus to reach specific chapters
  • Content must be 100% verbatim (no paraphrasing)

Prerequisites

  • delegate_task tool with browser toolset enabled
  • Target site URL (usually a single base URL with query-param navigation)
  • Mapping of questions/topics to specific book chapters

Workflow

Phase 1: Discovery (single browser session)

  1. Navigate to the base URL (e.g. https://ddc.shengyen.org/)
  2. Explore the tree menu structure. Note:
    • Which expandable levels exist (e.g. 輯 > 冊 > 章)
    • Whether chapters are loaded via javascript:void(null) links (they usually are)
    • Whether the URL changes when clicking chapters (it usually doesn't — content loads via AJAX)
  3. Test browser_console to extract content:
    document.querySelector('[class*="content"]')?.innerText || document.body.innerText.substring(0, 5000)
    
  4. Identify any bot detection early. If the site blocks, try different URL paths.

Phase 2: Batch Spawn (parallel extraction)

Divide the chapters into batches of 5-9 questions each. Each batch spawns a delegate_task with toolsets: ["browser"].

Critical passing of context:

  • Provide the EXACT chapter names and book numbers (e.g. 05-02 正信的佛教)
  • Provide output format template
  • Set max_iterations=40-55 for 6-9 chapters
  • Include site navigation instructions in the context

Context template:

HOW TO USE THE SITE:
1. Go to https://ddc.shengyen.org/
2. Click "第五輯 佛教入門類" in left sidebar to expand
3. Click the book (e.g. "05-03 學佛群疑") to expand its chapters
4. Click a chapter name from the expanded sub-menu
5. Use browser_console: document.querySelector('[class*="content"]')?.innerText || ...
6. Copy the EXACT text, verbatim

QUESTIONS TO EXTRACT:
{list of questions with book and chapter mapping}

Output format for EACH question:
## Question: {question}
**Source**: 《書名》聖嚴法師 — Chapter Name
**Original Text**:
> {exact, verbatim, can be long}

Read the full file on GitHub · 118 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 · 118 lines · 51 tokens per session scan A acd5dd1ef435

Subscribe to this mod's changes

multi-agent-browser-text-extraction is a skill published in the GitHub repository ChrisLamDev/hermes-core-skills (9 stars, last pushed 2mo ago), licensed MIT. It adds 51 tokens to every session and 1,175 once invoked, about $0.0003 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.