Aumai Pii Redactor

B+ 86 completed
Cli Tool
cli / python · tiny
30
Files
4,323
LOC
1
Frameworks
4
Languages

Pipeline State

completed
Run ID
#304033
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
35.02
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #47626
Member of a group with 2 similar repo(s) — canonical #93576 view group →
Top concepts (5)
Project DescriptiontestingTestingDatabaseTesting
Repobility · open methodology · https://repobility.com/research/

AI Prompt

Build me a command-line tool in Python that automatically detects and redacts personally identifiable information (PII) from agent telemetry data. I need the core functionality to be robust, and I should be able to follow the provided documentation structure for getting started. Please ensure the project is set up with pytest for testing and includes necessary configuration files like pyproject.toml.
python cli pii redaction ai telemetry pytest command-line
Generated by gemma4:latest

Catalog Information

This project detects and redacts personally identifiable information (PII) in agent telemetry.

Description

Aumai PII Redactor is a tool that automatically identifies and removes sensitive data from agent logs. It uses machine learning algorithms to detect patterns indicative of PII, such as names, addresses, and phone numbers. The tool is designed for use in security and compliance applications where protecting user privacy is crucial.

الوصف

هذا الأداة تحدد وتحذف المعلومات الشخصية المحددة (PII) من التелемتري لل एजنت. تستخدم هذه الأداة خوارزميات التعلم الآلي لتحديد الأنماط التي تشير إلى PII، مثل الأسماء والعناوين والرقم الهاتفي. مصممة لهذا الغرض في تطبيقات الأمن والموافقة حيث ضروري حماية الخصوصية للمستخدم.

Novelty

5/10

Tags

pii-detection data-redaction agent-telemetry security-compliance privacy-protection

Technologies

click pydantic

Claude Models

claude-opus-4.6

Quality Score

B+
86.2/100
Structure
92
Code Quality
88
Documentation
85
Testing
85
Practices
70
Security
100
Dependencies
80

Strengths

  • CI/CD pipeline configured (github_actions)
  • Good test coverage (88% test-to-source ratio)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected
  • Properly licensed project

Security & Health

4.6h
Tech Debt (C)
Medium
DORA Rating
A
OWASP (100%)
Repobility — same analyzer, your code, free for public repos · /scan/
PASS
Quality Gate
A
Risk (2)
Apache-2.0
License
5.0%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
50.9%
markdown
45.8%
yaml
1.7%
toml
1.6%

Frameworks

pytest

Symbols

variable36
function14
method13
class9
constant1

Concepts (5)

Repobility · code-quality intelligence · https://repobility.com
CategoryNameDescriptionConfidence
All rows scored by the Repobility analyzer (https://repobility.com)
auto_descriptionProject Description> Automatic PII detection and redaction in agent telemetry80%
arch_layertestingDetected testing layer70%
auto_categoryTestingtesting70%
business_logicDatabaseDetected from 2 related files50%
business_logicTestingDetected from 7 related files50%

Quality Timeline

1 quality score recorded.

View File Metrics
Repobility · MCP-ready · https://repobility.com

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BinComp Dependency Hardening

All packages →
2 of this repo's dependencies have been scanned for binary hardening. Grade reflects RELRO / stack canary / FORTIFY / PIE coverage.
Nclick8.3.2 · 0 gadgets · risk 0.0Npydantic2.12.5 · 0 gadgets · risk 0.0