djm204

60 mods across 1 repository, 2 stars between them.

code-quality-1

01

djm204/frankenbeast

Cursor rule Cursor

Code quality standards - SOLID, DRY, clean code practices, naming, error handling, immutability. Universal across languages and frameworks.

2 6d ago A 417 tokens

code-quality

02

djm204/frankenbeast

Cursor rule Cursor

Code quality standards - SOLID, DRY, clean code practices, naming, error handling, immutability. Universal across languages and frameworks.

2 6d ago A 417 tokens

communication

03

djm204/frankenbeast

Cursor rule Cursor

Communication guidelines - direct, honest, objective interaction when assisting with development. Tone, code communication, avoiding common issues.

2 6d ago A 318 tokens

core-principles-1

04

djm204/frankenbeast

Cursor rule Cursor

Core principles - honesty over output, simplicity, tests required, professional objectivity, incremental progress. Universal guidance for all development.

2 6d ago A 477 tokens

core-principles

05

djm204/frankenbeast

Cursor rule Cursor

Core principles - honesty over output, simplicity, tests required, professional objectivity, incremental progress. Universal guidance for all development.

2 6d ago A 477 tokens

gemini-cli

06

djm204/frankenbeast

Cursor rule Cursor

Guidelines for AI-assisted development using Gemini CLI.

2 6d ago A 305 tokens

git-workflow

07

djm204/frankenbeast

Cursor rule Cursor

Git workflow - commits, branching, PRs, safety rules. Universal git practices for clean, traceable project history.

2 6d ago A 389 tokens

djm204/frankenbeast

Cursor rule Cursor

Cursor rule "javascript-expert-testing" from djm204/frankenbeast, covering javascript testing, unit tests, component tests, mocking (msw for apis) and e2e tests (playwright).

2 6d ago A 3 tokens

ml-ai-deployment

17

djm204/frankenbeast

Cursor rule Cursor

ML deployment—real-time vs batch, KServe/Triton, scaling, versioning, rollback. Package model and deps; same preprocessing as training.

2 6d ago A 31 tokens

djm204/frankenbeast

Cursor rule Cursor

Model development—experiment tracking, metrics, evaluation by segment, hyperparameter tuning. Reproducibility; version data, code, config.

2 6d ago A 28 tokens

ml-ai-monitoring

19

djm204/frankenbeast

Cursor rule Cursor

ML monitoring—data and concept drift, performance tracking, latency and throughput. Evidently/WhyLabs-style checks; alerts on degradation.

2 6d ago A 27 tokens

ml-ai-security

21

djm204/frankenbeast

Cursor rule Cursor

ML security and responsible AI—input validation, adversarial robustness, fairness, explainability. Data poisoning, extraction, abuse; NIST-aligned.

2 6d ago A 30 tokens

ml-ai-testing

22

djm204/frankenbeast

Cursor rule Cursor

ML testing - data validation, transform parity, model behavior, integration. Statistical correctness; train/serve consistency.

2 6d ago A 22 tokens