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 agentmods add skills/lasywolf/learn-openclaw/pdfnpx skills add lasywolf/Learn-OpenClaw --skill pdfgit clone --depth 1 https://github.com/lasywolf/Learn-OpenClawWhat 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 | $0.00092 | $0.02082 |
| Opus 5 | $0.00046 | $0.01041 |
| Sonnet 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 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.
This is a copy
89% identical to pdf — 15 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 2.7 KB runs code
- scripts/check_fillable_fields.py 268 B runs code
- scripts/convert_pdf_to_images.py 1008 B runs code
- scripts/create_validation_image.py 1.2 KB runs code
- scripts/extract_form_field_info.py 4.2 KB runs code
- scripts/extract_form_structure.py 3.9 KB runs code
- scripts/fill_fillable_fields.py 3.7 KB runs code
- scripts/fill_pdf_form_with_annotations.py 3.2 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.
- 3d ago First seen · 315 lines · 92 tokens per session scan A 9f78b8359fbd
pdf is a skill published in the GitHub repository lasywolf/Learn-OpenClaw (544 stars, last pushed 17d ago), licensed MIT. It adds 92 tokens to every session and 2,082 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to pdf, differing in 15 lines, and is treated as a copy.
Other skills, from other repositories
skill-doc-delivery
Convert markdown to DOCX, PPTX, XLSX, PDF office documents — use when you need exportable deliverables.
document-gen-resilient
Multi-path document generation with tool checks, Unicode handling, and Python fallbacks.
pdf-explore
Read, extract, and cross-check content across scientific PDFs. Use when a task needs methods, figures, tables, citations, accessions, or claims from multiple places in one or more papers.
make-resume
中文可编辑简历制作技能:根据用户经历选择或复刻模板,生成可编辑 HTML 简历并提供 PDF 导出;当用户输入“/make-resume”或要求制作、修改、复刻简历文件时使用。.
paper-reader
Use when user asks to "read paper", "analyze paper", "summarize paper", "读论文", "分析文献", "帮我看一下这篇paper", "论文笔记", or provides a PDF file that appears to be an academic paper. Specialized for CV/DL papers. Also supports Zotero integration: "读一下这篇论文 ...", "快速看一下这篇论文 ...", "批判性分析这篇论文 ...", "读一下 Zotero 里的 XXX", "批量读一下 Zotero…
decrypt4pdf
对加密的 PDF 文件进行解密。当用户提到 PDF 解密、解除 PDF 密码、解 PDF 时使用。.