Skip to main content

English | Tiếng Việt

Vietnamese Writing Skills

Live Web App CI Python 3.11–3.14 License: MIT

🌐 Live Web Application: https://vietnamese-humanizer-g1o9.vercel.app/

Tools for editing Vietnamese prose without changing its facts. They help make writing clearer, more natural, and consistent with its context.

This repository is named vietnamese-humanizer because that is its project URL. The product is called Vietnamese Writing Skills because it contains four skills, not just a humanizer. Its Python distribution is vietnamese-writing-skills; import it as vietnamese_writing_skills.

The project does not classify authorship, produce an "AI probability score," or offer detector-evasion advice. Its linter reports surface signals for a person to review.

Four skills

Skill Use it when Do not use it when
humanizer-vi Prose feels templated, clichéd, flat in rhythm, or uneven in voice Inferring authorship, evading detectors, or doing only mechanical proofreading
translationese-cleaner-vi Vietnamese copies English word order, metaphors, or nominalization too closely Replacing established terms or weakening legal language
grammar-checker-vi Checking spelling, punctuation, structure, or ambiguity Imposing a style or changing code, URLs, or identifiers
style-guide-vi Keeping pronouns, terms, numbers, and formatting consistent Overriding a project style guide or changing facts

Fact-preserving example

Before:

Trong bài viết này, chúng ta sẽ cùng tìm hiểu cách Redis lưu dữ liệu thường dùng trong bộ nhớ để giảm số lần truy cập nguồn dữ liệu chậm hơn.

After:

Redis lưu dữ liệu thường dùng trong bộ nhớ, nhờ đó hệ thống ít phải truy cập nguồn dữ liệu chậm hơn.

This edit removes only the announcement. The input already states the Redis mechanism, so an editor must not replace it with a broad claim such as "Redis improves performance." Corpus entries must state any information outside the input in context.

Four output modes

  • clean_rewrite: A fact-preserving rewrite that can replace the input.
  • review_comment: Feedback for an author when evidence or sources are missing, not replacement text.
  • needs_author_decision: The input has multiple plausible readings, so the author decides before editing.
  • no_change: The input is already suitable. Do not change it merely for variety.

An agent does not need to rewrite every input. It should decline to guess when the subject, scope, date, or level of obligation is unclear.

Run the web app locally

Python 3.11+, Node.js 20.9+, and npm are required. From a source checkout, the primary quickstart is:

python3 scripts/dev.py demo

The command checks the local prerequisites, creates or repairs .venv, installs the root and backend development packages, runs npm ci, and starts the backend and frontend. It is safe to run again. Open http://localhost:3000; press Ctrl-C to stop both servers.

The local demo intentionally disables rewrite, contribution, and admin capabilities. Lint remains available without provider credentials or a database. See the web guide for capability-specific environment variables and the maintainer guide for repository checks and release work.

Install Agent Skills

The fastest way to add these skills to an AI agent (such as Cursor, Claude Code, Antigravity, Windsurf, or VS Code) is using npx skills:

# Add all 4 skills from this repository
npx skills add longhang2004/vietnamese-humanizer

# Or add a specific skill (e.g. humanizer-vi)
npx skills add longhang2004/vietnamese-humanizer --skill humanizer-vi

Alternatively, install manually from a git checkout:

git clone https://github.com/longhang2004/vietnamese-humanizer.git
cd vietnamese-humanizer

Point an Agent Skills-compatible client at the needed directory under skills/, or copy that directory into the client's skill location. Each one includes SKILL.md, references, and any required assets.

Example request:

Use humanizer-vi to edit this email. Keep the professional tone and preserve
every number, product name, condition, and deadline.

Install the Python CLI

Python 3.11 or newer is required. Install from a source checkout:

python -m pip install .

Build and install a wheel:

python -m pip install build
python -m build
python -m pip install dist/*.whl

Install for development:

python -m pip install -e ".[dev]"

The wheel includes patterns, schemas, skill Markdown, examples, and benchmark resources. When it finds a surrounding repository, the CLI uses that repository by default. Pass --root PATH to choose another checkout. Outside a repository, pattern-reading commands use the resources bundled in the wheel.

Console commands

viet-writing-lint article.md
viet-writing-lint article.md --format json
viet-writing-lint docs/ --recursive --root .
viet-writing-validate-skills --root .
viet-writing-validate-patterns --root .
viet-writing-validate-examples --root .
viet-writing-benchmark --root . --validate-only
viet-writing-generate-docs --root . --check

Source checkouts also retain these legacy wrappers:

python scripts/lint_vietnamese.py article.md
python scripts/validate_skills.py
python scripts/validate_patterns.py
python scripts/validate_examples.py
python scripts/run_benchmarks.py --validate-only
python scripts/generate_pattern_docs.py --check

The linter exits with 1 when it finds material to review and 2 when it cannot run. A finding does not prove that prose is wrong or AI-generated.

Linter taxonomy

  • ERROR: A relatively demonstrable error, such as an accidental repeated word or invalid spacing.
  • WARNING: A structure that may be ambiguous or inconsistent but requires context.
  • PREFERENCE: A style choice that should only be applied after a style has been selected.
  • HEURISTIC: A surface signal such as density or sentence rhythm; a reviewer must inspect the full scope.

Patterns also define scope and aggregation. Repeated sentence openings, for example, use paragraph/sequence; sentence rhythm uses document/variance; mixed pronouns use document/consistency.

Corpus and benchmark

The catalog has 43 patterns with finding type, scope, aggregation, exceptions, and false-positive risk. Its 100 examples specify an output mode, context, must_preserve, must_not_add, and review provenance. The 30 benchmark cases record an expected output mode, context, specific blockers, and preservation constraints. JSON Schema validates manual-review results, and a case may have several reviewers.

A coding agent audited each input + context → output pair in the corpus. agent-reviewed does not mean reviewed by a maintainer, native speaker, or independent reviewer. The repository has no independent baseline yet. The current benchmark helps with process design and data regression; it does not establish effectiveness outside these authored cases.

Check the repository

ruff check .
pytest
python scripts/validate_skills.py
python scripts/validate_patterns.py
python scripts/validate_examples.py
python scripts/run_benchmarks.py --validate-only
python scripts/generate_pattern_docs.py --check
python -m build

Regenerate the pattern documentation after editing YAML:

python scripts/generate_pattern_docs.py

Contributing

Read CONTRIBUTING.md, the Code of Conduct, the documentation index, and the pattern authoring guide. New examples need enough input and context for verification, explicit preservation and no-addition constraints, an output mode, and accurate review provenance. New patterns need a taxonomy, scope, aggregation behavior, exceptions, tests, and examples that add no facts.

Limitations

Regexes and structural validators cannot prove semantic equivalence. They can miss problems or produce false positives. One hundred examples cannot represent every regional, generational, professional, or register difference. See limitations and evaluation methodology.

Support the project

If Vietnamese Writing Skills is useful, you can make an optional donation to support maintenance. Before confirming a transfer, verify that the recipient is HANG NHUT LONG at BIDV.

VietQR donation code for HANG NHUT LONG at BIDV

Contributors and acknowledgments

  • Hàng Nhựt Long (@longhang2004) — Core maintainer & developer.
  • Lê Ngọc Phương Thư (lengocphuongthuct2006@gmail.com) — Suggested and ideated the web application version.

The project draws on the Agent Skills specification, style-audit ideas from blader/humanizer, and localization work in Chinese and Korean projects. The Vietnamese taxonomy and data in this repository were written independently. Details are in the research notes.

Original code and content are released under the MIT License. See ROADMAP.md for planned work.

Metadata

Release files for vietnamese-writing-skills 0.4.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for vietnamese-writing-skills 0.4.3
File Size Uploaded
vietnamese_writing_skills-0.4.3.tar.gz 2.1 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for vietnamese-writing-skills 0.4.3
File Interpreter ABI Platform
vietnamese_writing_skills-0.4.3-py3-none-any.whl Python 3 none any Details

Total release size: 2.2 MB

Release files / vietnamese_writing_skills-0.4.3.tar.gz

Download URL vietnamese_writing_skills-0.4.3.tar.gz
Size 2.1 MB
Tags Source
SHA-256 checksum
How to use checksums
43da201d104139385dedcb79c20038ef3d9d880916566736c147948f20c33abe
BLAKE2b-256 checksum
How to use checksums
715033bebc0c2a5f924b09c5cbc5b30a4e0443c2fcd0adacd8d7b92f519c8605
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Jul 22, 2026.

Transparency log

Release files / vietnamese_writing_skills-0.4.3-py3-none-any.whl

Download URL vietnamese_writing_skills-0.4.3-py3-none-any.whl
Size 108.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
296a22cbfdaf18360ecdac4e7b565490da501e01256b3a68455ca28fd0fdfe33
BLAKE2b-256 checksum
How to use checksums
96aee53652c5ddaa9d96b40e60d7417a964dbaaf33cf75b92b39f5302c08f895
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Jul 22, 2026.

Transparency log

Release history Release notifications | RSS feed

0.4.6

2 release files

0.4.5

2 release files

0.4.4

2 release files

This release

0.4.3 This release

2 release files

0.4.2

2 release files

0.4.1

2 release files

0.4.0

2 release files

0.3.1

2 release files

0.3.0

2 release files

0.2.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page