Pdf tools

Skill event4u-app/agent-config/dist/agent-src/skills/pdf-tools

Universal AI Agent OS — audited skills, governance rules, replayable state. One contract, every host agent.

Install

npx -y skills add event4u-app/agent-config --skill pdf-tools

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

7 stars7 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Use when creating, merging, splitting, filling, or extracting from a PDF — library-per-task, output validated. Triggers on 'merge these PDFs', 'fill this PDF form', 'split the PDF', 'create a PDF'.

SKILL.md

4.3 KB, 945 tokens by cl100k_base, as published. Nobody here has run it

pdf-tools

Wing-1 engineering skill for PDF write/transform — markitdown reads a PDF to Markdown; this creates, merges, fills, and extracts. Ships zero runtime: the agent drives libraries the consumer has. Pattern re-implementation only.

When to use

"Merge / split / rotate / encrypt these PDFs."
"Fill this PDF form (AcroForm) with these values."
"Create a PDF from this content."
"Extract the text / tables from this PDF" (structured extraction beyond markitdown's Markdown).
"OCR this scanned PDF."

Do NOT use for: PDF → Markdown ingestion (markitdown); Word (docx-authoring).

Procedure

1. Library per task — do not force one tool

Task	Library path
merge / split / rotate / encrypt	pypdf — page-level operations, no rendering
create from content	reportlab (canvas / platypus)
form-fill (AcroForm)	a form-aware library; map field name → value, then flatten if the form must not be re-editable
text / table extraction	a text-layer extractor; tables need a layout-aware pass, not naive text
OCR (scanned/image PDF)	an OCR engine over rasterized pages — ONLY when there is no text layer

2. Decide flatten-or-keep on form fills

A filled AcroForm stays editable unless flattened. Flatten when the PDF is a final artifact (an invoice, a signed form); keep fields when the recipient must edit further. State which you chose — a silently-editable "final" form is a correctness bug.

3. Validate — assert output validity, do not trust the write

Re-open the output with pypdf; assert len(reader.pages) matches the expected count (merge = sum; split = 1 per part).
For a form-fill: read back one field value (pre-flatten) or extract the rendered text (post-flatten) and assert the value is present.
For create: assert the file opens and page 1 carries expected text.

Output format

The output PDF path(s).
Validation: page count matches expected ✅, read-back value/text present ✅.
For fills: flatten decision stated (flattened / kept-editable + why).

Gotcha

OCR is a last resort, not the default extraction path. Running OCR over a PDF that already has a text layer produces worse output (OCR errors) than the existing text and burns time. Check for a text layer first; OCR only when it is genuinely absent.

Editable "final" form: a filled AcroForm left un-flattened ships as a "signed invoice" the recipient can silently alter → flatten when the artifact is final.

Do NOT

Do NOT bundle a Python toolkit in this package — drive the consumer's libraries (zero-runtime posture).
Do NOT OCR a PDF that has a text layer.
Do NOT leave a "final" filled form editable without saying so.
Do NOT claim success on "file written"; claim it only after the re-open + page-count assertion.

Related Skills

WHEN to use this

The task creates, merges, splits, rotates, encrypts, or form-fills a PDF.
Structured text/table extraction beyond markitdown's Markdown, or OCR of a scanned PDF.

WHEN NOT to use this

PDF → Markdown ingestion → markitdown.
Word documents → docx-authoring; spreadsheets → spreadsheet-authoring.

When the agent should load this

"Merge / split / rotate these PDFs."
"Fill this PDF form."
"Create a PDF from this content."
"Extract the tables from this PDF / OCR this scan."

Output

Output PDF(s) — the path(s). Cite as pdf-output.
Validation receipt — page count matches expected ✅, read-back value/text present ✅. Cite as pdf-validation.
Fill decision — present on form-fills: flattened / kept-editable + why. Cite as pdf-fill-decision.

Gives 0 of the 12 instructions most pdf office docs skills give in 945 tokens

Counted across 635 of the 690 authors here whose files we hold, read 2026-08-06

extract text using pdfplumberin 92 of 635, across 25 files
create PDFs using reportlabin 83 of 635, across 16 files
read FORMS.md to fill out PDF formsin 80 of 635, across 13 files
OCR scanned PDFs using pytesseractin 77 of 635, across 10 files
merge or split PDFs using qpdfin 70 of 635, across 3 files
use Excel formulas instead of hardcoded calculated valuesin 68 of 635, across 12 files
unpack edit xml and repack existing documentsin 63 of 635, across 8 files
document sources for hardcoded valuesin 61 of 635, across 9 files
write minimal python code without unnecessary commentsin 59 of 635, across 7 files
run the recalculation script after adding or modifying formulasin 58 of 635, across 6 files
fix all identified formula errors and recalculatein 58 of 635, across 6 files
format years as text stringsin 57 of 635, across 5 files

Said here and by no other author read

select one library per task
flatten final forms or state the decision
reopen output and assert page count
assert expected text or field value is present

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.