SkillsBench is a benchmark for measuring how effectively AI agents use modular skills—folders containing instructions, scripts, and resources—to complete specialized tasks. It helps researchers and developers evaluate both skill quality and agent behavior, including tasks that require combining multiple skills. The catalogue’s skills and instructions are evaluated as part of this workflow.
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/benchflow-ai/skillsbench/pdfnpx skills add benchflow-ai/skillsbench --skill pdfgit clone --depth 1 https://github.com/benchflow-ai/skillsbenchWrote 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/benchflow-ai/skillsbench/pdf)<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/pdf"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/pdf.svg" alt="Measured on agentmods" 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 | $0.00029 | $0.02193 |
| Opus 5 | $0.00015 | $0.01097 |
| Sonnet 5 | $0.00006 | $0.00439 |
| Haiku 4.5 | $0.00003 | $0.00219 |
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 6d 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
1 near-identical copy found in the catalogue:
- skill-003 — 95% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 331 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PDF Processing Guide
Overview
Extract text/tables, create PDFs, merge/split files, fill forms using Python libraries and command-line tools. Apply this skill for programmatic document processing and analysis. For advanced features or form filling, consult reference.md and forms.md.
Visual Enhancement with Scientific Schematics
When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.
If your document does not already contain schematics or diagrams:
- Use the scientific-schematics skill to generate AI-powered publication-quality diagrams
- Simply describe your desired diagram in natural language
- Nano Banana Pro will automatically generate, review, and refine the schematic
For new documents: Scientific schematics should be generated by default to visually represent key concepts, workflows, architectures, or relationships described in the text.
How to generate schematics:
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
The AI will automatically:
- Create publication-quality images with proper formatting
- Review and refine through multiple iterations
- Ensure accessibility (colorblind-friendly, high contrast)
- Save outputs in the figures/ directory
When to add schematics:
- PDF processing workflow diagrams
- Document manipulation flowcharts
- Form processing visualizations
- Data extraction pipeline diagrams
- Any complex concept that benefits from visualization
For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
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)
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 9.2 KB
- LICENSE.txt 1.4 KB
- reference.md 16 KB
- scripts/check_bounding_boxes_test.py 8.5 KB runs code
- scripts/check_bounding_boxes.py 3.1 KB runs code
- scripts/check_fillable_fields.py 362 B runs code
- scripts/convert_pdf_to_images.py 1.1 KB runs code
- scripts/create_validation_image.py 1.5 KB runs code
- scripts/extract_form_field_info.py 6.0 KB runs code
- scripts/fill_fillable_fields.py 4.7 KB runs code
- scripts/fill_pdf_form_with_annotations.py 3.4 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.
- 6d ago First seen · 331 lines · 29 tokens per session scan A 582cc779d71a
pdf is a skill published in the GitHub repository benchflow-ai/skillsbench (1,747 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 29 tokens to every session and 2,193 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
document-organization-pipeline
End-to-end pipeline for extracting, classifying, and organizing documents by subject.
pdf-calendar-parsing
Extract calendar events, blocks, and time slots from PDF calendar files using pdfplumber.
file-organizer-by-subject
Organize files into subject folders using keyword-based classification of titles and abstracts, with fallback to full text extraction.
pdf-form-filling
Fill PDF form fields programmatically using Python libraries like pypdf or pdfrw.
pdf-text-extraction
Extract text content from PDF files for analysis and classification.
pdf-inspection
Techniques for inspecting PDF form fields and their properties using Python libraries like pypdf.