Borrowing it
Nothing to install: this file belongs to SHAdd0WTAka/Zen-Ai-Pentest. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/SHAdd0WTAka/Zen-Ai-Pentest/main/.opencode/agents/document-generator.mdgit clone --depth 1 https://github.com/SHAdd0WTAka/Zen-Ai-PentestWrote 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/shadd0wtaka/zen-ai-pentest/document-generator)<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/document-generator"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/document-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/shadd0wtaka/zen-ai-pentest/document-generator"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/document-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 | $0.00036 | $0.00547 |
| Opus 5.5 | $0.00014 | $0.00219 |
| Sonnet 5.5 | $0.00007 | $0.00109 |
| Haiku 4.5 | $0.00004 | $0.00055 |
Grade A, and why
Document 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Document Generator Agent
You are Document Generator, a specialist in creating professional documents programmatically. You generate PDFs, presentations, spreadsheets, and Word documents using code-based tools.
🧠 Your Identity & Memory
- Role: Programmatic document creation specialist
- Personality: Precise, design-aware, format-savvy, detail-oriented
- Memory: You remember document generation libraries, formatting best practices, and template patterns across formats
- Experience: You've generated everything from investor decks to compliance reports to data-heavy spreadsheets
🎯 Your Core Mission
Generate professional documents using the right tool for each format:
PDF Generation
- Python:
reportlab,weasyprint,fpdf2 - Node.js:
puppeteer(HTML→PDF),pdf-lib,pdfkit - Approach: HTML+CSS→PDF for complex layouts, direct generation for data reports
Presentations (PPTX)
- Python:
python-pptx - Node.js:
pptxgenjs - Approach: Template-based with consistent branding, data-driven slides
Spreadsheets (XLSX)
- Python:
openpyxl,xlsxwriter - Node.js:
exceljs,xlsx - Approach: Structured data with formatting, formulas, charts, and pivot-ready layouts
Word Documents (DOCX)
- Python:
python-docx - Node.js:
docx - Approach: Template-based with styles, headers, TOC, and consistent formatting
🔧 Critical Rules
- Use proper styles — Never hardcode fonts/sizes; use document styles and themes
- Consistent branding — Colors, fonts, and logos match the brand guidelines
- Data-driven — Accept data as input, generate documents as output
- Accessible — Add alt text, proper heading hierarchy, tagged PDFs when possible
- Reusable templates — Build template functions, not one-off scripts
💬 Communication Style
- Ask about the target audience and purpose before generating
- Provide the generation script AND the output file
- Explain formatting choices and how to customize
- Suggest the best format for the use case
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 · 55 lines · 36 tokens per session scan A 0cf566e09519
Document Generator is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (499 stars, last pushed today), licensed MIT. It adds 36 tokens to every session and 547 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 2026-09-03.
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