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 jakkaj/tools --skill htmlify-v2git clone --depth 1 https://github.com/jakkaj/toolsWrote 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/jakkaj/tools/htmlify-v2)<a href="https://agentmods.dev/skills/jakkaj/tools/htmlify-v2"><img src="https://agentmods.dev/badge/skills/jakkaj/tools/htmlify-v2/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/skills/jakkaj/tools/htmlify-v2"><img src="https://agentmods.dev/badge/skills/jakkaj/tools/htmlify-v2.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 | $0.00038 | $0.04228 |
| Opus 5.5 | $0.00015 | $0.01691 |
| Sonnet 5.5 | $0.00008 | $0.00846 |
| Haiku 4.5 | $0.00004 | $0.00423 |
Grade A, and why
htmlify-v2 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 2mo 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 — 414 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Please deep think / ultrathink as this is a complex task.
htmlify-v2
Static HTML document generator — takes any content the user points to (markdown files, notes, specs, plans, conversation context) and produces a polished, self-contained HTML file. Zero dependencies, opens directly in a browser, ready to share or print to PDF.
User input:
$ARGUMENTS
Expected usage patterns:
```bash
/htmlify <source> # HTMLify a file or path
/htmlify <source> --output path/to/out.html # Specify output path
/htmlify # HTMLify from conversation context
/htmlify --dark # Use dark variant
```
Where `<source>` can be:
- A file path (markdown, text, any readable file)
- A directory (concatenates relevant files)
- Omitted — uses the current conversation context or the user's description
Purpose
Produce beautiful, zero-dependency static HTML documents from raw content. The output should look like a polished report you'd share with stakeholders — not a raw markdown render. Think Notion page or Linear changelog — clean, readable, professional.
Flow
1) Parse Arguments
- Determine the source content (file path, directory, or conversation context)
- Determine the output path (default: same directory as source, with
.htmlextension; for context-based, use./scratch/or current directory) - Determine theme (default: light;
--darkfor dark variant)
2) Load & Analyse Source Content
- Read the source content fully
- Identify the document structure:
- Title and subtitle
- Sections and their hierarchy
- Tables, lists, code blocks
- Diagrams (mermaid candidates)
- Key findings, recommendations, callouts
- Metrics or summary data
- Determine which components best represent each content element
3) Generate HTML
Rules:
- Use semantic HTML throughout — real HTML elements, NOT markdown rendered at runtime
- First line of the output file MUST be:
<!-- Generated by htmlify-v2 --> - All CSS is inlined in a
<style>block — single self-contained file - Select appropriate accent colours from the palette to visually distinguish sections
- Use callout variants to match tone (see palette below)
- Use tables for structured comparisons — don't force everything into cards
- Add anchor navigation bar if the document has 3+ sections
- Include mermaid diagrams where content describes flows, architectures, or relationships
- Add mermaid.js CDN script ONLY if mermaid diagrams are present
- Preserve the substance and detail of the source — don't summarise or truncate
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.
- 2mo ago First seen · 414 lines · 38 tokens per session scan A e9e27225f200
htmlify-v2 is a skill published in the GitHub repository jakkaj/tools (5 stars, last pushed 24d ago), licensed MIT. It adds 38 tokens to every session and 4,228 once invoked, about $0.0002 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 2026-08-31.
htmlify-v2 compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| htmlify-v2jakkaj/tools | Skill | 5 | 24d ago | MIT | A | 38 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 4d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |