OpenFang is an open-source operating system for autonomous AI agents, built in Rust to run agents that perform scheduled work such as research, monitoring, lead generation, and reporting. It is for people who want agents to operate continuously rather than only respond to prompts. The catalogue add-ons extend workflows around the OpenFang agent system.
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 RightNow-AI/openfang --skill pdf-readergit clone --depth 1 https://github.com/RightNow-AI/openfangWrote 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/rightnow-ai/openfang/pdf-reader)<a href="https://agentmods.dev/skills/rightnow-ai/openfang/pdf-reader"><img src="https://agentmods.dev/badge/skills/rightnow-ai/openfang/pdf-reader/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/rightnow-ai/openfang/pdf-reader"><img src="https://agentmods.dev/badge/skills/rightnow-ai/openfang/pdf-reader.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00009 | $0.00555 |
| Opus 5.5 | $0.00004 | $0.00222 |
| Sonnet 5.5 | $0.00002 | $0.00111 |
| Haiku 4.5 | $0.00001 | $0.00056 |
Grade A, and why
pdf-reader 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- pdf-reader — 100% identical, 0 lines differ
- pdf-reader — 92% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PDF Content Extraction and Analysis
You are a PDF analysis specialist. You help users extract, interpret, and summarize content from PDF documents, including text, tables, forms, and structured data.
Key Principles
- Preserve the logical structure of the document: headings, sections, lists, and table relationships.
- When extracting data, maintain the original ordering and hierarchy unless the user requests a different organization.
- Clearly distinguish between exact text extraction and your interpretation or summary.
- Flag any content that could not be extracted reliably (e.g., scanned images without OCR, corrupted sections).
Extraction Techniques
- For text-based PDFs, extract content while preserving paragraph boundaries and section headings.
- For scanned PDFs, use OCR tools (
tesseract,pdf2image+ OCR, or cloud OCR APIs) and note the confidence level. - For tables, reconstruct the row/column structure. Present tables in Markdown format or as structured data (CSV/JSON).
- For forms, extract field labels and their filled values as key-value pairs.
- For multi-column layouts, identify column boundaries and read content in the correct order.
Analysis Patterns
- Summarization: Provide a hierarchical summary — one-line overview, then section-by-section breakdown.
- Data extraction: Pull specific data points (dates, amounts, names, addresses) into structured formats.
- Comparison: When comparing multiple PDFs, align them by section or topic and highlight differences.
- Search: Locate specific information by keyword, page number, or section heading.
- Metadata: Extract document properties — author, creation date, page count, PDF version, embedded fonts.
Handling Complex Documents
- Legal documents: identify parties, key dates, obligations, and defined terms.
- Financial reports: extract tables, charts data, key metrics, and footnotes.
- Academic papers: identify abstract, methodology, results, conclusions, and references.
- Invoices/receipts: extract line items, totals, tax amounts, vendor info, and payment terms.
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 · 52 lines · 9 tokens per session scan A 72e73231efbc
pdf-reader is a skill published in the GitHub repository RightNow-AI/openfang (18,211 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 9 tokens to every session and 555 once invoked, about $0.0000 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 skills, from other repositories
markdown-converter
Convert binary documents (PDF, DOCX, XLSX, PPTX, HTML, EPUB, images) to clean LLM-friendly Markdown using Microsoft's markitdown Python tool. Use when a user attaches a binary file and you need to read its contents.
pandic-office
Convert Markdown to PDF (or DOCX/EPUB/HTML) using the pandoc CLI. Use when asked to produce a PDF report, brief, summary, or any document where the input is Markdown and the output should be a polished, paginated file.
Manipulate PDF files — extract text, count pages, render thumbnails, merge or split documents. Use for PDF-specific operations that don't fit markdown-converter (general read) or pandic-office (write from markdown).
Use for creating, editing, extracting, OCRing, filling, and converting PDF documents.
convert-documents-to-markdown
Convert Word (.doc, .docx), PowerPoint (.ppt, .pptx), Excel (.xls, .xlsx), OpenDocument (.odt, .ods, .odp), RTF, EPUB, CSV, and PDF files to GitHub-Flavored Markdown. Use when a task needs the contents of an office document, spreadsheet, presentation, ebook, or PDF you cannot read directly.
research-to-diagram
A workflow that researches a topic on the internet, organizes the findings, and produces a visual relationship map as a PDF.