
SPARC Architecture Implementation
FreeStreamline your algorithm design and architecture planning.
Free · Opens the source repo
What SPARC Architecture Implementation does
The SPARC Architecture Implementation skill facilitates the execution of Phases 2 and 3 of the SPARC methodology, focusing on algorithm design and architectural planning. This skill is particularly useful for developers and designers who have completed the Specification phase and are ready to translate requirements into actionable pseudocode and architectural designs. By systematically structuring the development process, this skill ensures that the resulting implementation is both efficient and maintainable.
In Phase 2, users can write language-agnostic pseudocode that aligns with acceptance criteria, define core data structures, and map control flows, including error handling and concurrent access scenarios. The skill also emphasizes documenting algorithmic complexity, providing a comprehensive overview of the design. This structured approach not only aids in clarity but also serves as a reference for future development.
Moving into Phase 3, the skill guides users through establishing module boundaries and API contracts, ensuring that the architecture adheres to best practices such as Domain-Driven Design (DDD). Users will define bounded contexts, aggregate roots, and domain events, alongside specifying infrastructure concerns like persistence strategies and messaging patterns. By storing these artifacts, the skill creates a clear path from design to implementation, making it easier to transition into writing production code.
This skill is designed for developers and teams who prioritize structured development processes and wish to enhance their workflow by integrating algorithm design with architectural considerations. It is particularly beneficial in collaborative environments where clear documentation and adherence to specifications are critical for project success.
When to use it
Use this skill after completing the Specification phase to ensure your implementation is well-structured and aligned with project requirements.
When not to use it
This skill may not be suitable for projects that require rapid prototyping or when the specifications are not well-defined.
What you can build with it
Transitioning from Specification to Implementation
After finalizing the specifications, use this skill to create structured pseudocode and architectural designs that guide your implementation.
Collaborative Development Environments
In team settings, utilize this skill to ensure all developers are aligned on the architecture and algorithms, enhancing communication and reducing errors.
Documenting Complex Systems
For projects with intricate requirements, this skill helps document the architecture and algorithms, making it easier to onboard new team members and maintain the codebase.
How to install SPARC Architecture Implementation
View source1. Install with the skills CLI
npx skills add ruvnet/ruflo/sparc-implement --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by ruvnetSPARC Architecture + Implementation
Run Phases 2 and 3 of the SPARC methodology: design algorithms with pseudocode, then establish architecture with module boundaries and API contracts.
When to use
After the Specification phase is complete and its gate has been passed. This skill covers both the Pseudocode and Architecture phases as they are tightly coupled — algorithm design informs module boundaries and vice versa.
Steps
-
Retrieve specification — call
mcp__plugin_ruflo-core_ruflo__memory_searchwith namespacesparc-phasesand query for the feature's spec. Extract requirements, acceptance criteria, constraints, and edge cases. -
Retrieve phase state — call
mcp__plugin_ruflo-core_ruflo__memory_searchwith namespacesparc-stateand query for the feature to confirm we are in Phase 2 or 3. -
Search for architectural patterns — call
mcp__plugin_ruflo-core_ruflo__neural_predictwith the feature description to find relevant architectural decisions from past projects -
Phase 2 — Pseudocode Design: a. For each acceptance criterion, write language-agnostic pseudocode that satisfies it b. Define core data structures with type annotations c. Map control flow including:
- Happy path
- Error/exception paths for each edge case
- Concurrent access handling if applicable d. Annotate algorithmic complexity (time and space) for critical paths e. Store pseudocode artifact:
- Call
mcp__plugin_ruflo-core_ruflo__memory_storewith namespacesparc-phases, keypseudo-{feature-slug} - Value:
{ status: "complete", algorithms: [...], dataStructures: [...], controlFlow: [...], complexity: {...} }
-
Phase 3 — Architecture Design: a. Define bounded contexts and aggregate roots following DDD patterns:
- Identify entity boundaries and value objects
- Define aggregate invariants
- Map domain events b. Design API contracts:
- Request/response schemas with TypeScript interfaces
- Error response codes and formats
- Versioning strategy if applicable c. Plan module boundaries:
- Directory structure
- Dependency direction rules (no circular dependencies)
- Public vs internal interfaces d. Specify infrastructure concerns:
- Persistence strategy (database, cache, file)
- Messaging patterns (sync, async, event-driven)
- Configuration and environment requirements e. Store architecture artifact:
- Call
mcp__plugin_ruflo-core_ruflo__memory_storewith namespacesparc-phases, keyarch-{feature-slug} - Value:
{ status: "complete", boundedContexts: [...], apiContracts: [...], moduleBoundaries: {...}, infrastructure: {...} }
-
Update phase state — call
mcp__plugin_ruflo-core_ruflo__memory_storewith namespacesparc-state, updating current phase to 3 (Architecture) with both artifacts recorded -
Record trajectory step — call
mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-stepwith architecture summary -
Begin implementation — if the user confirms, proceed to write production code: a. Create files following the defined module boundaries b. Implement interfaces and types first c. Implement core logic following the pseudocode d. Write unit tests alongside implementation (TDD when possible) e. Run tests to verify acceptance criteria
-
Present architecture — display the architecture decision record and suggest running
/sparc advanceto pass the Phase 3 gate
Output format
# Pseudocode: {Feature Name}
## Core Algorithms
### Algorithm 1: {name}
```pseudocode
FUNCTION processRequest(input):
VALIDATE input against schema
IF invalid THEN THROW ValidationError
result <- TRANSFORM input
STORE result
RETURN result
Complexity: O(n) time, O(1) space
Data Structures
- {StructName}: { field1: type, field2: type }
Architecture: {Feature Name}
Bounded Contexts
- {ContextName}: {description}
- Aggregates: {list}
- Events: {list}
API Contracts
POST /api/{resource}
- Request: { field1: string, field2: number }
- Response: { id: string, ...fields }
- Errors: 400 (validation), 409 (conflict), 500 (internal)
Module Structure
src/{feature}/
{feature}.types.ts # Interfaces and types
{feature}.service.ts # Business logic
{feature}.controller.ts # HTTP handling
{feature}.repository.ts # Data access
{feature}.test.ts # Tests
Infrastructure
- Persistence: {strategy}
- Caching: {strategy}
- Events: {strategy}
Phases 2-3 complete. Run /sparc advance to pass the gate check.
Frequently asked questions about SPARC Architecture Implementation
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