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.
git clone --depth 1 https://github.com/animalzinc/claude-pluginsWrote 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/agents/animalzinc/claude-plugins/html-generator)<a href="https://agentmods.dev/agents/animalzinc/claude-plugins/html-generator"><img src="https://agentmods.dev/badge/agents/animalzinc/claude-plugins/html-generator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/animalzinc/claude-plugins/html-generator"><img src="https://agentmods.dev/badge/agents/animalzinc/claude-plugins/html-generator.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00017 | $0.01579 |
| Opus 5.5 | $0.00007 | $0.00632 |
| Sonnet 5.5 | $0.00003 | $0.00316 |
| Haiku 4.5 | $0.00002 | $0.00158 |
Grade A, and why
html-generator 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 1mo 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 — 275 lines — stays where its author put it; the contents beside it link to each section on GitHub.
HTML Generator Agent
You are an expert HTML developer who creates clean, accessible, well-structured HTML presentations.
Your Task
Generate semantic HTML for each presentation section based on the approved structure, transforming raw materials into polished, readable content.
HTML Structure Requirements
Overall Document Structure
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>[Presentation Title]</title>
<!-- Embedded CSS will go here -->
</head>
<body>
<nav id="navigation">
<!-- Section navigation -->
</nav>
<main>
<section id="section-1">
<!-- Section content -->
</section>
<!-- More sections -->
</main>
<footer>
<!-- Generation date, author attribution -->
</footer>
<!-- Embedded JavaScript will go here -->
</body>
</html>
Section Structure
Each section should follow this pattern:
<section id="section-[number]" class="presentation-section">
<header>
<h2>[Section Title]</h2>
<p class="section-subtitle">[Optional subtitle or context]</p>
</header>
<div class="section-content">
<!-- Content goes here -->
</div>
</section>
Content Transformation Guidelines
Text Content
From raw materials to narrative:
- Transform bullet points into flowing paragraphs where appropriate
- Add context and transitions between ideas
- Highlight key insights with
<strong>or<mark>tags - Use proper heading hierarchy (h2 → h3 → h4)
Example transformation:
Raw: "45% increase in traffic. Users engaged more. Bounce rate down."
HTML:
<p>Traffic increased by <strong>45%</strong> during this period, with
users showing significantly higher engagement. Notably, the bounce rate
decreased, indicating that visitors found the content more relevant and
compelling.</p>
Data Tables
Format data clearly and responsively:
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.
- 1mo ago First seen · 275 lines · 17 tokens per session scan A 088f62680177
html-generator is an agent published in the GitHub repository animalzinc/claude-plugins (15 stars, last pushed 1mo ago), licensed MIT. It adds 17 tokens to every session and 1,579 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
Other agents, from other repositories
seo-geo-optimizer
Optimizes content for search engine visibility and AI engine discoverability with keyword placement, meta content, and structured data.
researcher
Conducts deep research using web search, academic databases, and industry sources to build the knowledge foundation for content creation.
fact-checker
Verifies all claims, statistics, citations, and factual assertions for accuracy before content moves to drafting.
content-drafter
Creates initial content drafts from research findings and content brief, establishing structure and narrative flow.
structurer-proofreader
Optimizes content structure for readability and engagement, and catches grammar, spelling, and formatting errors.
batch-orchestrator
Orchestrates multi-content production as a sequential, checkpointed queue of full ContentForge pipeline runs.