Implementation strategy selection framework. Use when planning implementation strategy, selecting development approach, or defining verification criteria.
npx skills add https://github.com/shinpr/claude-code-workflows --skill implementation-approach
Core Question: "What does the existing implementation look like?"
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
Complete these steps in order before selecting an implementation strategy:
Failed Items with their evidence; record None when all pass. Report problems outside that boundary separately for a scope decision.Adopted Additions as addition → Failed Item → evidence that lower-surface resolutions fail; an addition requires a Failed Item.Rejected Additions with a brief reason; record None when step 3 had no rejected candidate.Classify supporting claims as observed, inferred, or unknown. When an unknown blocks the next step, stop at the current step and name the evidence or user decision required.
Design Doc output: Direct MVP, Failed Items, Adopted Additions, and Rejected Additions.
Core Question: "When determining before → after, what implementation patterns or strategies should be referenced?"
Direct Strategy: Smallest repository-supported change that satisfies the accepted requirements and constraints
Repository Alternatives: Existing patterns that materially differ in migration, dependency order, or verification boundary
External Research: Official/current sources only when repository evidence cannot resolve a time-sensitive capability, compatibility, or dependency decision
Legacy Handling Strategies:
New Development Strategies:
Integration/Migration Strategies:
Use these patterns only when their named migration or dependency problem exists. Start with the direct strategy. Compare an alternative when it would materially change risk, rollout, compatibility, or the early verification point; do not add a pattern or combination only to increase the option count.
Core Question: "What risks arise when applying this to existing implementation, and what's the best way to control them?"
Technical Risks: System impact, data consistency, performance degradation, integration complexity
Operational Risks: Service availability, deployment downtime, process changes, rollback procedures
Project Risks: Schedule delays, learning costs, quality achievement, team coordination
Preventive Measures: Phased migration, parallel operation verification, integration/regression tests, monitoring setup
Incident Response: Rollback procedures, log/metrics preparation, communication system, service continuation procedures
Core Question: "What are this project's constraints?"
Technical Constraints: Library compatibility, resource capacity, mandatory requirements, numerical targets
Temporal Constraints: Deadlines/priorities, dependencies, milestones, learning periods
Resource Constraints: Team/skills, work hours/systems, budget, external contracts
Business Constraints: Market launch timing, customer impact, regulatory compliance
Select the implementation approach that directly fits the verified dependency and delivery constraints:
Characteristics: Vertical implementation across all layers by feature unit
Application Conditions: Default when an end-to-end value unit can be delivered and verified independently. Sharing fewer than 2 data models or touching 3+ layers are supporting signals, not substitutes for independent deliverability
Verification Method: End-user value delivery at each feature completion
Characteristics: Phased construction by architecture layer
Application Conditions: Use when a common foundation blocks consumer work or must pass stability/compatibility verification before dependent slices can proceed. Three or more dependent features is a mandatory signal to evaluate this approach
Verification Method: Integrated operation verification when all foundation layers complete
Characteristics: Flexible combination according to project characteristics
Application Conditions: Use when a verified foundation step is required first and later work can proceed as independently verifiable value slices. Resolve blocking requirement ambiguity before selecting the implementation approach
Verification Method: Verify at appropriate L1/L2/L3 levels according to each phase's goals
Design Doc Documentation: Record in the Design Doc's implementation approach section:
Priority for completion verification of each task:
Priority: L1 > L2 > L3 in order of verifiability importance
Define integration points according to selected strategy:
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Comprehensive technology-agnostic prompt for analyzing and documenting project folder structures. Auto-detects project types (.NET, Java, React, Angular, Python, Node.js, Flutter), generates detailed blueprints with visualization options, naming conventions, file placement patterns, and extension templates for maintaining consistent code organization across diverse technology stacks.
Use when complex problems require systematic step-by-step reasoning with ability to revise thoughts, branch into alternative approaches, or dynamically adjust scope. Ideal for multi-stage analysis, design planning, problem decomposition, or tasks with initially unclear scope.
Multi-agent workflow examples to work together on the OpenServ Platform. Covers agent discovery, multi-agent workspaces, task dependencies, and workflow orchestration using the Platform Client. Read reference.md for the full API reference. Read openserv-agent-sdk and openserv-client for building and running agents.
> Compress natural language memory files (CLAUDE.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md.
API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination.
Patterns for automating GitHub workflows with AI assistance, inspired by [Gemini CLI](https://github.com/google-gemini/gemini-cli) and modern DevOps practices.
Groups existing components into logical business domains to plan service-based architecture. Use when asking "which components belong together?", "group these into services", "organize by domain", "component-to-domain mapping", or planning service extraction from an existing codebase. Do NOT use for identifying new domains from scratch (use domain-analysis) or analyzing coupling (use coupling-analysis).
Take shinpr/implementation-approach from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.