24 boosters for "sdlc" — open source, verified from GitHub, ready to install
A skill for executing pre-written implementation plans with critical review and checkpoint validation, ideal for breaking complex tasks into separate sessions with human oversight.
A TDD-based framework for creating and validating AI agent skills through test-driven documentation and pressure testing. Developers building Claude Code agents or multi-agent systems benefit from this systematic approach to skill development and deployment.
Helps developers create isolated git worktrees for parallel feature development without disrupting their current workspace. Essential for teams managing multiple branches simultaneously.
A collaborative design-first booster that guides developers through brainstorming and specification before implementation, preventing premature coding and misaligned requirements.
Guides developers through the final stages of completing a development branch by verifying tests pass and presenting structured options for merging, creating PRs, or cleanup. Useful for developers who want a systematic approach to integrating completed work.
This booster enforces mandatory skill tool invocation at the start of conversations to establish available capabilities. It's designed for users who want to ensure AI assistants always discover and declare applicable skills before responding.
A skill that generates detailed, bite-sized implementation plans for multi-step tasks before coding begins, designed for engineers unfamiliar with the codebase. Useful for teams wanting structured planning and onboarding guidance.
This booster dispatches a code-reviewer subagent to catch issues before merging, promoting early and frequent code review practices. It benefits developers using claude_code who want to maintain code quality throughout their workflow.
Helps developers critically evaluate code review feedback by verifying technical soundness before implementation, preventing blind acceptance of potentially incorrect suggestions.
A skill booster that structures implementation execution by dispatching independent subagents for each task with two-stage review (spec compliance, then code quality), designed for developers managing multi-task implementation plans in a single session.
Enables concurrent investigation of multiple independent tasks by dispatching separate agents to each problem domain, saving time on parallel debugging and testing workflows.
Guides AI coding assistants to follow Test-Driven Development principles by writing failing tests before implementation code. Useful for developers who want to maintain code quality and ensure comprehensive test coverage.
This booster enforces a disciplined verification workflow that prevents false success claims by requiring developers to run and confirm verification commands before marking work complete. It's essential for any development team wanting to eliminate premature PRs and false positives.
A debugging methodology booster that enforces root-cause analysis before proposing fixes, helping developers avoid quick patches that mask underlying issues. Useful for anyone working with code in Claude who needs structured debugging processes.
Cognitive architecture for AI-augmented software development. Specialized agents, structured workflows, and multi-platform deployment. Claude Code · Codex · Copilot · Cursor · Factory · Warp · Windsurf.
"name": "alfred-dev", "description": "Plugin de ingeniería de software completa: 10 agentes de núcleo y 8 opcionales con personalidad propia, memoria persistente por proyecto, quality gates y flujos automatizados desde la idea hasta producción.", "homepage": "https://alfred-dev.com",
"name": "wicked-garden", "description": "AI-Native SDLC \u2014 the complete software development lifecycle as a single Claude Code plugin. 14 domains covering code intelligence, delivery metrics, persistent memory, workflow orchestration, brainstorming, on-demand personas, and 80 specialist agents a
A coding agent designed for enterprise teams managing long-running projects, enabling incremental feature development with state management across multiple sessions and context windows. Ideal for DevOps engineers, engineering managers, and development teams working within compliance-heavy environments (HIPAA, SOC2).
Fixer is an agentic workflow that applies targeted, minimal fixes derived from code and test critiques, generating a traceable fix summary artifact. It benefits developers in CI/CD pipelines who need fast, surgical code corrections without full refactoring.
An intelligent agent selection system that evaluates and ranks AI agents for different SDLC phases, enabling teams to automatically match optimal agents to tasks with confidence scoring and human oversight. Ideal for organizations managing multi-phase software development pipelines with diverse agent capabilities.
A multi-agent orchestration system that designs team compositions, manages shared context, and coordinates handoffs to drive complex SDLC phase deliverables to completion. Teams building large-scale software projects benefit from its conflict resolution and convergence mechanisms.
Cursor rules booster providing structured guidance for implementing LangGraph nodes, edges, and graph definitions with logging best practices. Helps developers building AI agent POCs ensure consistent, maintainable graph architecture.
Heuristic scoring (no AI key configured).
