# flytkgl/PDFQFZ

PDF加盖骑缝章的小工具

Repository: https://github.com/flytkgl/PDFQFZ
Canonical: https://ross.abutalabs.com/products/pdfqfz
Language: C#
License Family: other
Last push: 2026-06-12T13:19:49+00:00

## Health v2 (maintenance only)
Score: 90/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 87, release rhythm 88, longevity 100
- inputs: {"age_days": 3069, "days_push": 82, "days_rel": 82, "gap_med": 21.5, "n_releases_24m": 7}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2003, forks 254 (observed 2026-08-28T04:06:04.561265+00:00)

## What it is
PDFQFZ is a small desktop tool for adding cross-page (riding) seals to PDF documents. It takes a full seal image, randomly splits it across the pages of a PDF, and saves the stamped file to a chosen folder.

## Use cases
- stamp a riding seal across all pages of a pdf
- batch stamp pdf files in a folder with a company seal
- split a seal image across pdf pages automatically
- add official seal to signed pdf documents
- customize seal size and position on pdf pages

## When to choose
- you need to apply Chinese-style cross-page seals to PDFs
- you want a simple GUI tool for batch stamping PDF files
- you need automatic random splitting of a seal image across pages

## When to avoid
- you need digital cryptographic signatures rather than visual stamps
- you require cross-platform or command-line operation
- you need a maintained library to integrate stamping into your own code

## Facets
- artifact type: application
- maturity: active
- function: pdf, image-processing
- domain: pdf, files, developer-tools
- platform: windows
- tags: pdf-stamping, seal-stamp, cross-page-stamp, chinese-seal, document-processing, desktop

## Member repositories
- flytkgl/PDFQFZ (main) score 90

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:04.561265+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:01:55.240340+00:00, confidence not recorded.
  - readme: https://github.com/flytkgl/PDFQFZ (fetched 2026-08-28T04:06:04.561265+00:00, sha f0c0719cfbaa)
- Data as of 2026-08-30T08:39:29.467469+00:00.