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AVRA-CADAVRA AI Skills

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Browse published AI skills maintained by AVRA-CADAVRA. Compare skill descriptions and follow each source repository for setup instructions.

Author statistics

Indexed skills

60

Repository stars across indexed skills

0

Repository forks

0

Average repository stars per indexed skill

0

Repository stars may repeat across skills from the same repository.

60 skills

Browse skills

GitHub

test-quality-enforcement

AVRA-CADAVRA

Enforces test quality standards: behavior-focused tests, no property-only tests, round-trip JSON, comprehensive test blocks. Use when writing tests, reviewing test code, or ensuring test quality.

GitHub

experiment-testing-standards

AVRA-CADAVRA

Enforces experiment testing standards: real implementation testing, no simplified approximations, exact formula matching. Use when creating experiments, testing algorithms, or validating mathematical implementa...

GitHub

integration-test-patterns

AVRA-CADAVRA

Guides integration test patterns: end-to-end workflows, cross-layer testing, real dependencies, no mocks unless approved. Use when writing integration tests, testing complete features, or validating system inte...

GitHub

widget-test-patterns

AVRA-CADAVRA

Guides widget test patterns: BLoC testing, user interactions, state changes, material app setup. Use when writing widget tests, testing UI components, or validating widget behavior.

GitHub

test-implementation-requirements

AVRA-CADAVRA

Enforces test implementation requirements: real dependencies, no mocks/stubs unless approved. Use when writing tests, reviewing test implementations, or ensuring tests use real functionality.

GitHub

test-coverage-requirements

AVRA-CADAVRA

Enforces test coverage requirements: models (100%), repositories (95%), BLoCs (100%), use cases (100%), services (90%). Use when writing tests, reviewing test coverage, or ensuring adequate test coverage.

GitHub

test-template-generation

AVRA-CADAVRA

Generates test templates: unit, widget, integration, service tests following project patterns. Use when creating new tests or ensuring tests follow project standards.

GitHub

logging-standards-enforcement

AVRA-CADAVRA

Enforces mandatory logging standards using developer.log() instead of print(). Use when writing production code, reviewing code, or fixing logging violations.

GitHub

file-organization-standards

AVRA-CADAVRA

Enforces file naming conventions, directory structure, one class per file, Clean Architecture layer placement. Use when creating new files, organizing code, or refactoring file structure.

GitHub

linter-error-prevention

AVRA-CADAVRA

Enforces zero linter errors, common issue prevention, code cleanup. Use when writing code, reviewing code, or ensuring code quality standards.

GitHub

code-documentation-standards

AVRA-CADAVRA

Enforces Dart doc comments for public APIs, parameter descriptions, usage examples. Use when writing public APIs, reviewing code, or ensuring documentation completeness.

GitHub

spots-philosophy-integration

AVRA-CADAVRA

Ensures all code aligns with SPOTS core philosophy: "Doors, not badges", meaningful connections, real-world enhancement. Use when implementing features, reviewing code, or making architectural decisions to vali...

GitHub

import-organization

AVRA-CADAVRA

Enforces import grouping (Dart SDK → Flutter → packages → relative), alphabetical order, unused import removal. Use when writing or reviewing code to ensure consistent import organization.

GitHub

security-validation-checklist

AVRA-CADAVRA

Guides security validation checklist: Signal protocol security, encryption standards, authentication patterns, data protection. Use when validating security, reviewing security implementations, or ensuring secu...

GitHub

privacy-protection-patterns

AVRA-CADAVRA

Enforces privacy protection patterns: anonymization, no PII in logs, secure data handling, GDPR compliance. Use when handling user data, implementing AI2AI, or ensuring privacy compliance.

GitHub

status-query-handling

AVRA-CADAVRA

Guides status query handling protocol: find all related documents (plan, progress, status, complete), synthesize comprehensive answer. Use when user asks about status, progress, or completion.

GitHub

expertise-system-implementation

AVRA-CADAVRA

Guides expertise system implementation: multi-path recognition, hierarchy (local → city → state → national), golden experts, visit quality. Use when implementing expertise calculations, expert recognition, or e...

GitHub

plan-discovery-workflow

AVRA-CADAVRA

Guides plan discovery workflow: glob search, recency filtering, relevance assessment, priority reading. Use when starting new tasks, finding related plans, or gathering context.

GitHub

hybrid-search-implementation

AVRA-CADAVRA

Guides hybrid search implementation: vector embeddings, keyword search, fusion algorithms, caching strategies. Use when implementing search, recommendation systems, or discovery features.

GitHub

dependency-injection-getit

AVRA-CADAVRA

Guides GetIt dependency injection patterns for service registration. Use when creating new services, registering dependencies, or refactoring service architecture.

GitHub

design-tokens-enforcement

AVRA-CADAVRA

Enforces design token usage (AppColors/AppTheme) instead of direct Colors.*. Use when writing UI code, reviewing widgets, or ensuring design consistency.

GitHub

quantum-matching-algorithms

AVRA-CADAVRA

Guides quantum matching implementation: state calculations, compatibility formulas, quantum entanglement matching patterns. Use when implementing matching algorithms, compatibility calculations, or quantum stat...

GitHub

ai2ai-learning-service

AVRA-CADAVRA

Guides AI2AI learning service implementation: personality spectrum, compatibility calculations, learning methods, anonymous data exchange. Use when implementing AI2AI learning, personality evolution, or peer le...

GitHub

business-partnership-patterns

AVRA-CADAVRA

Guides business partnership implementation: multi-party events, revenue sharing, vibe matching, pre-event agreements. Use when implementing partnerships, event collaborations, or revenue sharing features.

The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.