sparc-methodology
SPARC methodology for multi-agent development: systematic Specification, Pseudocode, Architecture, Refinement, and Completion workflows via Claude Flow orchestration.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
203 skills found
SPARC methodology for multi-agent development: systematic Specification, Pseudocode, Architecture, Refinement, and Completion workflows via Claude Flow orchestration.
End-to-end startup idea validation using S.E.E.D. niche checks, STREAM 6-layer analysis, and Devil's Advocate inversion to generate PRDs.
Orchestrate end-to-end quality engineering across CI/CD pipelines, from commit-stage unit testing and shift-left strategies to production-stage synthetic monitoring and compliance gates.
Multi-model LLM integration patterns for Claude, GPT, Gemini, and Ollama. Features API handling, prompt engineering, token management, and model-agnostic orchestration.
Fetches expert perspectives from OpenAI Codex and Google Gemini for architecture, code reviews, and debugging, with transparent LLM synthesis.
Expert guidance for building production-ready applications with Anthropic's Claude API. Covers SDKs, prompt caching, batch processing, streaming, tool use, and cost optimization strategies.
Enforces low Cognitive and Cyclomatic complexity in all code. Automatically maintains readability, modularity, and maintainability by preventing complex functions during development.
A standardized workflow for converting raw PM notes, workshops, or rough drafts into polished, validated, and repository-compliant AI skills.
Shopify integration to manage e-commerce data, products, orders, and customer workflows using Membrane CLI.
Autonomous multi-team codebase improvement agent with specialized modes: narrow (goal-directed), broad (hypothesis-divergent), and sweep (quality-focused).
Analyze search results (SERP) to classify user intent, identify feature opportunities, and conduct competitive intelligence for content strategy.
Build and orchestrate end-to-end MLOps pipelines covering data preparation, training, validation, and automated deployment.