Eigent is an open-source desktop application for creating and running teams of AI agents that automate complex workflows locally. It supports focused tasks and coordinated multi-agent work for people who want a free, customizable AI workforce.
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 eigent-ai/eigent --skill pdfgit clone --depth 1 https://github.com/eigent-ai/eigentWrote 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/eigent-ai/eigent/pdf)<a href="https://agentmods.dev/skills/eigent-ai/eigent/pdf"><img src="https://agentmods.dev/badge/skills/eigent-ai/eigent/pdf/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/eigent-ai/eigent/pdf"><img src="https://agentmods.dev/badge/skills/eigent-ai/eigent/pdf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00092 | $0.02082 |
| Opus 5.5 | $0.00037 | $0.00833 |
| Sonnet 5.5 | $0.00018 | $0.00416 |
| Haiku 4.5 | $0.00009 | $0.00208 |
Grade A, and why
pdf 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.
This is a copy
100% identical to pdf — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 315 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PDF Processing Guide
Overview
This guide covers essential PDF processing operations using Python libraries and command-line tools. For advanced features, JavaScript libraries, and detailed examples, see REFERENCE.md. If you need to fill out a PDF form, read FORMS.md and follow its instructions.
Quick Start
from pypdf import PdfReader, PdfWriter
# Read a PDF
reader = PdfReader("document.pdf")
print(f"Pages: {len(reader.pages)}")
# Extract text
text = ""
for page in reader.pages:
text += page.extract_text()
Python Libraries
pypdf - Basic Operations
Merge PDFs
from pypdf import PdfWriter, PdfReader
writer = PdfWriter()
for pdf_file in ["doc1.pdf", "doc2.pdf", "doc3.pdf"]:
reader = PdfReader(pdf_file)
for page in reader.pages:
writer.add_page(page)
with open("merged.pdf", "wb") as output:
writer.write(output)
Split PDF
reader = PdfReader("input.pdf")
for i, page in enumerate(reader.pages):
writer = PdfWriter()
writer.add_page(page)
with open(f"page_{i+1}.pdf", "wb") as output:
writer.write(output)
Extract Metadata
reader = PdfReader("document.pdf")
meta = reader.metadata
print(f"Title: {meta.title}")
print(f"Author: {meta.author}")
print(f"Subject: {meta.subject}")
print(f"Creator: {meta.creator}")
Rotate Pages
reader = PdfReader("input.pdf")
writer = PdfWriter()
page = reader.pages[0]
page.rotate(90) # Rotate 90 degrees clockwise
writer.add_page(page)
with open("rotated.pdf", "wb") as output:
writer.write(output)
pdfplumber - Text and Table Extraction
Extract Text with Layout
import pdfplumber
with pdfplumber.open("document.pdf") as pdf:
for page in pdf.pages:
text = page.extract_text()
print(text)
Extract Tables
with pdfplumber.open("document.pdf") as pdf:
for i, page in enumerate(pdf.pages):
tables = page.extract_tables()
for j, table in enumerate(tables):
print(f"Table {j+1} on page {i+1}:")
for row in table:
print(row)
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- forms.md 12 KB
- LICENSE.txt 1.4 KB
- reference.md 16 KB
- scripts/check_bounding_boxes.py 3.4 KB runs code
- scripts/check_fillable_fields.py 963 B runs code
- scripts/convert_pdf_to_images.py 1.7 KB runs code
- scripts/create_validation_image.py 1.9 KB runs code
- scripts/extract_form_field_info.py 4.9 KB runs code
- scripts/extract_form_structure.py 4.5 KB runs code
- scripts/fill_fillable_fields.py 4.4 KB runs code
- scripts/fill_pdf_form_with_annotations.py 3.8 KB runs code
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 · 315 lines · 92 tokens per session scan A 9f78b8359fbd
pdf is a skill published in the GitHub repository eigent-ai/eigent (15,589 stars, last pushed today), licensed Apache-2.0. It adds 92 tokens to every session and 2,082 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to pdf, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
document-processor
Guidance for processing documents, extracting content, and transforming structured information. Use when the user asks to process, parse, extract, or transform document content such as PDFs, Word files, or spreadsheets.
word-cloud
Generate static or animated word clouds from any text source (PDF, DOCX, XLSX, PPTX, HTML, CSV, TXT), with theming, sentiment coloring and shape masks.
office-documents-official
Hint for Office and PDF file work. Use when the user asks to create, edit, read or convert a Word .docx, PDF, PowerPoint .pptx or Excel .xlsx file. caddis does not ship these skills; points to Anthropic's official document-skills plugin.
PDF toolkit: extract text and tables, create, merge and split PDFs, fill forms. Use to process, generate or analyze PDF documents.
foundry-hosted-agent-validation
Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.
moai-docs-generation
Documentation generation patterns for technical specs, API docs, user guides, and knowledge bases using real tools like Sphinx, MkDocs, TypeDoc, and Nextra. Use when creating docs from code, building doc sites, or automating documentation workflows.