Pipeworks Name Generation

C+ 73 completed
Library
unknown / python · small
462
Files
97,511
LOC
1
Frameworks
12
Languages

Pipeline State

completed
Run ID
#370444
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
42.80
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #47778
Member of a group with 1 similar repo(s) — canonical #22814 view group →
Top concepts (2)
Project DescriptionTesting
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AI Prompt

Create a corpus linguistics toolkit in Python for developers and world-builders. I need command-line tools to extract, analyze, and explore phonetic patterns and syllabic structure from any text source. The system should include phonetic feature analysis, data provenance tracking via a corpus database, and visualization utilities like t-SNE. Additionally, please include the lightweight, deterministic name generator as a reference implementation to show how to use the processed data for creating pronounceable names for games. The project should be testable using pytest.
python corpus linguistics nlp command-line phonetics name-generation toolkit pytest
Generated by gemma4:latest

Catalog Information

Generates phonetically-grounded names for use in games and procedural systems.

Description

Pipeworks-name-generation is a tool that generates names based on their phonetic properties, making it suitable for use in games and procedural systems where realistic-sounding names are required. It leverages various libraries such as matplotlib, numpy, pandas, plotly, and scikit-learn to analyze and manipulate data. The project aims to provide a reliable method for generating names that sound natural and authentic.

الوصف

هذا الأداة تُنشئ أسماءً بناءً على خصائصها الصوتية، مما يجعلها مناسبة للاستخدام في الألعاب والمواقع الإجرائية التي تتطلب أسماء تبدو واقعية. تستخدم هذه الأداة مكتبات متعددة مثل matplotlib, numpy, pandas, plotly, و scikit-learn للتحليل والتعديل على البيانات. يهدف المشروع إلى تقديم طريقة موثوقة لإنشاء أسماء تبدو طبيعية ومصدقة.

Novelty

7/10

Tags

name-generation phonetic-analysis game-development procedural-systems natural-language-processing

Technologies

matplotlib numpy pandas plotly scikit-learn

Claude Models

claude-opus-4.5 claude-opus-4.6 claude-sonnet-4.5

Quality Score

C+
73.4/100
Structure
82
Code Quality
64
Documentation
90
Testing
75
Practices
57
Security
75
Dependencies
60

Strengths

  • CI/CD pipeline configured (github_actions)
  • Good test coverage (49% test-to-source ratio)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Properly licensed project

Weaknesses

  • 5029 duplicate lines detected \u2014 consider DRY refactoring
  • 18 'god files' with >500 LOC need decomposition

Security & Health

11.6h
Tech Debt (A)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (0)
Repobility · open methodology · https://repobility.com/research/
AGPL-3.0
License
7.0%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
78.9%
javascript
5.8%
restructuredtext
4.4%
css
3.9%
markdown
2.9%
html
2.2%
json
0.8%
text
0.6%
yaml
0.4%
toml
0.1%
shell
0.0%
ini
0.0%

Frameworks

pytest

Concepts (2)

Repobility · the analyzer behind every row · https://repobility.com
CategoryNameDescriptionConfidence
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auto_descriptionProject Description> A corpus linguistics toolkit for extracting, analyzing, and exploring phonetic patterns from any text source.80%
auto_categoryTestingtesting70%

Quality Timeline

1 quality score recorded.

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