Document Generator

Document Generator is an agent for Claude Code, OpenCode from SHAdd0WTAka/Zen-Ai-Pentest. It costs 36 tokens per session (547 once invoked), scanned A, original, MIT.

A code-based document creation specialist for producing PDFs, PowerPoint presentations, Word documents, and spreadsheets with formatting, charts, and data visualizations.

In plain words
What is it for?
Use it to generate reports, investor decks, compliance documents, and data-heavy spreadsheets.
Why use it?
It helps turn structured data or templates into consistently formatted files without creating each document by hand.

Agent for Claude CodeOpenCode

Written for OpenCode and Claude Code: installed under .opencode/, but also a Claude Code subagent (agents/*.md). Also seen: mentions subagents.

Good fit Use it to generate reports, investor decks, compliance documents, and data-heavy spreadsheets.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/shadd0wtaka/zen-ai-pentest/document-generator
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.

Clone the repo
git clone --depth 1 https://github.com/SHAdd0WTAka/Zen-Ai-Pentest

Made for: Claude Code, OpenCode.

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 Document Generator

README.md
[![agentmods](https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/document-generator.svg)](https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/document-generator)
Your own site
<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="Measured on agentmods" height="20"></a>
Per session 36 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 547 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 $0.00036 $0.00547
Opus 5 $0.00018 $0.00273
Sonnet 5 $0.00007 $0.00109
Haiku 4.5 $0.00004 $0.00055

Measured 3d ago against content hash 0cf566e09519, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

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 3d 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.

.opencode/agents/document-generator.md · 55 lines

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

  1. Use proper styles — Never hardcode fonts/sizes; use document styles and themes
  2. Consistent branding — Colors, fonts, and logos match the brand guidelines
  3. Data-driven — Accept data as input, generate documents as output
  4. Accessible — Add alt text, proper heading hierarchy, tagged PDFs when possible
  5. 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

Read the full file on GitHub · 55 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. 3d ago First seen · 55 lines · 36 tokens per session scan A 0cf566e09519

Subscribe to this mod's changes

Document Generator is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (449 stars, last pushed 3d ago), licensed MIT. It adds 36 tokens to every session and 547 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 2026-09-03.

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