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 alex-alecu/garden-desk --skill pdf-documentsgit clone --depth 1 https://github.com/alex-alecu/garden-deskWrote 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/alex-alecu/garden-desk/pdf-documents)<a href="https://agentmods.dev/skills/alex-alecu/garden-desk/pdf-documents"><img src="https://agentmods.dev/badge/skills/alex-alecu/garden-desk/pdf-documents/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/alex-alecu/garden-desk/pdf-documents"><img src="https://agentmods.dev/badge/skills/alex-alecu/garden-desk/pdf-documents.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00020 | $0.00342 |
| Opus 5 | $0.00010 | $0.00171 |
| Sonnet 5 | $0.00004 | $0.00068 |
| Haiku 4.5 | $0.00002 | $0.00034 |
Grade A, and why
pdf-documents 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 10d 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.
What it actually says
Library
Use the installed pypdf through python for reading and page work, and reportlab (Platypus) to create a PDF. Do not install packages.
Find The Files
Search /source recursively for files ending in .pdf, case-insensitive.
Recipe
from pypdf import PdfReader
reader = PdfReader(path)
for number, page in enumerate(reader.pages, start=1):
print(f"page {number}: {page.extract_text() or ''}")
Cite every fact by page number, using this same one-based numbering.
To create a PDF, build a ReportLab SimpleDocTemplate with Platypus flowables (headings, paragraphs, tables); it handles page breaks and margins for you.
Verify
Reopen the PDF you write with PdfReader and assert its page count and the text of each page you generated.
Gotchas
extract_text()can returnNoneon an image-only or scanned page; treat that as no text, not an error.- Set metadata with
PdfWriter.add_metadata()using slash-prefixed keys, for example{"/Title": "Report"}. - Derive every value from the actual source PDF; do not assume a fixed input file name.
- A rotated page can still report text in reading order; check
page.rotationif layout looks wrong. - Reopen and check page count, order, rotation, and metadata before you report the deliverable done.
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.
- 10d ago First seen · 39 lines · 20 tokens per session scan A 8424b1679b19
pdf-documents is a skill published in the GitHub repository alex-alecu/garden-desk (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 20 tokens to every session and 342 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 2026-08-31.
Other skills, from other repositories
Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and…
PDF files: create, read, merge, fill, OCR, edit text.
pdf-toolkit
Structured .pdf operations: extract text/tables, merge pages from multiple PDFs, split a PDF by page ranges, fill PDF form fields, and generate fresh PDFs from JSON. Trigger when the user wants programmatic PDF work without natural-language rewriting — examples: pull tables from a report, combine three PDFs, extract…
extracting-lab-tables
Detects and extracts tabular laboratory panels from PDFs, scans, and images into structured rows ready for OpenMed and FHIR. Use when the user has a CBC, CMP, lipid panel, or other lab report as a scanned image / PDF / spreadsheet and needs the test name, value, unit, reference range, and abnormal flag as clean rows.…
nano-pdf
Edit PDFs with natural-language instructions using the nano-pdf CLI.
liteparse
Use this skill when the user asks to parse, perform multi-format document conversion or spatially extract text from an unstructured file (PDF, DOCX, PPTX, XLSX, images, etc.) locally without cloud dependencies.