Selects implementation strategy (vertical slice, horizontal, or hybrid) with risk assessment. Use when planning feature implementation.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Implementation Strategy Selection Framework (Meta-cognitive Approach)
## Meta-cognitive Strategy Selection Process
### Phase 1: Decision-Sufficient Current State Analysis
**Core Question**: "What does the existing implementation look like?"
#### Analysis Framework
```yaml
Architecture Analysis: Responsibility separation, data flow, dependencies, technical debt
Implementation Quality Assessment: Code quality, test coverage, performance, security
Historical Context Understanding: Current form rationale, past decision validity, constraint changes, requirement evolution
```
#### Meta-cognitive Question List
- What is the true responsibility of this implementation?
- Which parts are business essence and which derive from technical constraints?
- What dependencies or implicit preconditions are unclear from the code?
- What benefits and constraints does the current design bring?
Stop when another current-state fact cannot change responsibility, reuse, option validity, total complexity, a contract, or verification.
…
The line at the top of this page pins the label git:20261014.578fed5, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
GET https://markdownregistry.com/api/v1/artifacts/art_tuql6jkkutbdml35
GET https://markdownregistry.com/api/v1/resolve?ref=shinpr/ai-coding-project-boilerplate/implementation-approach
GET https://markdownregistry.com/api/v1/blob/3abbb2893ad998dd6535430aa576badc5386c1a5ff9a9772c9af43dad9e20637
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
shinpr/ai-coding-project-boilerplate · .claude/skills-en/documentation-criteria/SKILL.md · Determines which PRD, ADR, UI Spec, Design Doc, and Work Plan a change requires and where each is stored. Use when…
shinpr/ai-coding-project-boilerplate · .claude/skills-en/frontend-typescript-rules/SKILL.md · Applies React/TypeScript type safety, component design, and state management rules. Use when implementing React…
shinpr/ai-coding-project-boilerplate · .claude/skills-en/frontend-typescript-testing/SKILL.md · Designs frontend tests using the repository's configured React test and browser harnesses, including RTL, MSW, Vitest…
shinpr/ai-coding-project-boilerplate · .claude/skills-en/integration-e2e-testing/SKILL.md · Selects and designs the smallest integration/E2E test set that proves accepted behavior at an observable boundary. Use…
shinpr/ai-coding-project-boilerplate · .claude/skills-en/requirement-convergence/SKILL.md · Separates the outcome a change must produce from the requirements proposed to reach it, records what the user excluded…
shinpr/ai-coding-project-boilerplate · .claude/skills-en/skill-optimization/SKILL.md · Evaluates and optimizes skill file quality using 9 content patterns and 10 editing principles. Use when creating…
shinpr/codex-workflows · .agents/skills/implementation-approach/SKILL.md · Selects the smallest sufficient implementation strategy and verification boundary from current requirements and…