Inkform v0.1.1 — first public release

npm installation update: use npm install -g @nazifbd/inkform. The matching scoped distribution is available in v0.1.2. npm rejected the original unscoped name; the archives below remain usable.

Inkform learns a reusable private handwriting profile from reviewed samples, creates a calibration proof, and uses that profile to produce printable vector PDFs. This is the first public release, under the MIT license.

• Local Python engine and agent skill, with reviewed source provenance and immutable profile versions.
• Sample-first training, smooth outline refinement, semantic text/math layout, and actual PDF checks.
• npm launcher with explicit environment setup and a standalone skill installer.
• Introduction and examples and contribution guidance.

Release assets include a Python wheel/source package, the npm tarball, a self-contained skill ZIP, and SHA-256 checksums. The skill ZIP includes its runtime; after extracting it, run node runtime/bin/inkform.mjs setup from the skill directory. The npm tarball can be installed with npm install -g ./inkform-0.1.1.tgz, followed by inkform setup and inkform skill install.

Validated with 165 Python tests, 7 Node tests, a clean packed-package installation, vector PDF rendering, and standalone skill reuse. GitHub CI passed on Linux and macOS. All release archives passed the public-data check.

Training uses reviewed exemplar geometry. Segmentation and geometry review still need an agent or person; connected cursive, learned word spacing, and physical resemblance need further work and print calibration. Public examples are synthetic and contain no personal handwriting.