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shinpr AI Skills

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

Author statistics

Indexed skills

49

Repository stars across indexed skills

6,254

Repository forks

818

Average repository stars per indexed skill

128

Repository stars may repeat across skills from the same repository.

49 skills

Browse skills

GitHub

implementation-approach

shinpr

Selects implementation strategy (vertical slice, horizontal, or hybrid) with risk assessment. Use when planning feature implementation.

GitHub

typescript-testing

shinpr

Frontend testing rules with Vitest, React Testing Library, and MSW. Includes coverage requirements, test design principles, and quality criteria. Use when writing frontend tests or reviewing test quality.

GitHub

documentation-criteria

shinpr

Documentation creation criteria including PRD, ADR, Design Doc, and Work Plan requirements with templates. Use when creating or reviewing technical documents, or determining which documents are required.

GitHub

typescript-rules

shinpr

React/TypeScript frontend development rules including type safety, component design, state management, and error handling. Use when implementing React components, TypeScript code, or frontend features.

GitHub

subagents-orchestration-guide

shinpr

Guides subagent coordination through implementation workflows. Use when orchestrating multiple agents, managing workflow phases, or determining autonomous execution mode. Defines scale determination, document r...

GitHub

testing-principles

shinpr

Language-agnostic testing principles including TDD, test quality, coverage standards, and test design patterns. Use when writing tests, designing test strategies, or reviewing test quality.

GitHub

ai-development-guide

shinpr

Technical decision criteria, anti-pattern detection, debugging techniques, and quality check workflow. Use when making technical decisions, detecting code smells, or performing quality assurance.

GitHub

coding-principles

shinpr

Language-agnostic coding principles for maintainability, readability, and quality. Use when implementing features, refactoring code, or reviewing code quality.

GitHub

implementation-approach

shinpr

Implementation strategy selection framework with meta-cognitive approach, verification levels, and integration point definitions. Use when planning implementation strategy, selecting development approach, or de...

GitHub

frontend-ai-guide

shinpr

Frontend-specific technical decision criteria, anti-patterns, debugging techniques, and quality check workflow. Use when making frontend technical decisions or performing quality assurance.

GitHub

task-analyzer

shinpr

Performs metacognitive task analysis and skill selection. Use when determining task complexity, selecting appropriate skills, or estimating work scale. Returns skills with confidence scores and metadata.

GitHub

integration-e2e-testing

shinpr

Integration and E2E test design principles, ROI calculation, test skeleton specification, and review criteria. Use when designing integration tests, E2E tests, or reviewing test quality.

GitHub

mcp-local-rag

shinpr

Provides score interpretation (< 0.3 good, > 0.5 skip), query optimization, and source naming for query_documents, ingest_file, ingest_data tools. Use this skill when working with RAG, searching documents, inge...

GitHub

testing-strategy

shinpr

Prioritizes tests based on ROI and critical user journeys. Use when: deciding test coverage, selecting test types, or budgeting effort.

GitHub

testing

shinpr

Applies TDD process, test quality criteria, and mock guidelines. Use when: writing unit tests, using mocks, or reviewing test quality.

GitHub

documentation-criteria

shinpr

Guides PRD, ADR, Design Doc, and Work Plan creation. Use when: planning features, writing specs, or creating technical documents.

GitHub

coding-rules

shinpr

Applies coding standards for clean, maintainable code. Use when: writing functions, handling errors, refactoring, or reviewing code style.

GitHub

ai-development-guide

shinpr

Detects code smells, anti-patterns, and debugging issues. Use when: fixing bugs, reviewing code quality, or refactoring.

GitHub

integration-e2e-testing

shinpr

Designs integration and E2E tests with mock boundaries. Use when: writing E2E tests, integration tests, or reviewing test quality.

GitHub

metacognition

shinpr

Validates approach and checks assumptions before/after tasks. Use when: starting work, encountering errors, or switching phases.

GitHub

implementation-approach

shinpr

Selects implementation strategy (vertical/horizontal/hybrid) with risk assessment. Use when: planning features or deciding development approach.

GitHub

knowledge-base

shinpr

Project-specific prompt optimization knowledge management. Use when storing or retrieving learned patterns from comparisons. Provides schema, extraction criteria, capacity management, and retention scoring.

GitHub

prompt-optimization

shinpr

Model-agnostic prompt analysis and optimization patterns based on 2025-2026 research. Use when analyzing prompts for issues or generating optimized versions. Provides 8 patterns (BP-001 through BP-008) and 3-st...

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.