PATAS - Pattern-Adaptive Anti-Spam System (Public Demo & Documentation)
active 2025-11-15 → 2025-11-17 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 3 days from 2025-11-15 to 2025-11-17. Pushes: 25 total, peak 14 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 19 total, peak 19 in a day. Comments: 0 total, peak 0 in a day. Stars: 1 total, peak 1 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| kiku-jw | 44 | 25 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
- Issue#2kiku-jw2025-11-16 23:31[DOCS] Create interactive tutorial for CLI demo showing pattern detection workflow
- Issue#10kiku-jw2025-11-16 23:30[RESEARCH] Research: BMAD (Behavioral Model for Anomaly Detection) integration patterns
- Issue#10kiku-jw2025-11-16 23:30[RESEARCH] Research: BMAD (Behavioral Model for Anomaly Detection) integration patterns
- Issue#10kiku-jw2025-11-16 23:30[RESEARCH] Research: BMAD (Behavioral Model for Anomaly Detection) integration patterns
- Issue#10kiku-jw2025-11-16 23:30[RESEARCH] Research: BMAD (Behavioral Model for Anomaly Detection) integration patterns
- Issue#6kiku-jw2025-11-16 23:30[RESEARCH] Explore integration with evolutionary algorithms (AlphaEvolve) for rule optimization
- Issue#6kiku-jw2025-11-16 23:30[RESEARCH] Explore integration with evolutionary algorithms (AlphaEvolve) for rule optimization
- Issue#6kiku-jw2025-11-16 23:30[RESEARCH] Explore integration with evolutionary algorithms (AlphaEvolve) for rule optimization
- Issue#6kiku-jw2025-11-16 23:30[RESEARCH] Explore integration with evolutionary algorithms (AlphaEvolve) for rule optimization
- Issue#6kiku-jw2025-11-16 23:30[RESEARCH] Explore integration with evolutionary algorithms (AlphaEvolve) for rule optimization
- Issue#5kiku-jw2025-11-16 23:30[IDEAS] Brainstorm: How to improve PATAS architecture for better ML integration
- Issue#5kiku-jw2025-11-16 23:30[IDEAS] Brainstorm: How to improve PATAS architecture for better ML integration
- Issue#5kiku-jw2025-11-16 23:30[IDEAS] Brainstorm: How to improve PATAS architecture for better ML integration
- Issue#4kiku-jw2025-11-16 23:30[ARCHITECTURE] Design plugin system for CLI demo to support multiple pattern detectors
- Issue#4kiku-jw2025-11-16 23:30[ARCHITECTURE] Design plugin system for CLI demo to support multiple pattern detectors
- Issue#4kiku-jw2025-11-16 23:30[ARCHITECTURE] Design plugin system for CLI demo to support multiple pattern detectors
- Issue#4kiku-jw2025-11-16 23:30[ARCHITECTURE] Design plugin system for CLI demo to support multiple pattern detectors
- Issue#4kiku-jw2025-11-16 23:30[ARCHITECTURE] Design plugin system for CLI demo to support multiple pattern detectors
- Issue#3kiku-jw2025-11-16 23:30[ML] Integrate lightweight ML model for spam classification in CLI demo
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 1 stars here means stars gained during the window, not the repo's star count.