Specification-driven development workflow with creation, validation, decomposition, execution, and automated review-fix loops
npx claudepluginhub betamatt/claude-plugins --plugin specGenerate a spec file for a new feature or bugfix
Break down a validated specification into actionable implementation tasks
Implement a validated specification with review-fix loops
End-to-end spec implementation with review loops - validates, decomposes, and executes sequentially
Analyzes a specification document to determine if it has enough detail for autonomous implementation
Fixes a specific code review issue. Prioritizes by severity: CRITICAL issues first (security, crashes, data loss), then IMPORTANT (performance, error handling). Called by task-executor after review identifies issues. <example> Context: Code review found a security vulnerability prompt: "Fix CRITICAL issue: SQL injection in user query at src/db/users.ts:42. Current code uses string concatenation for query building." assistant: "I'll analyze the vulnerability, implement parameterized queries, and verify the fix doesn't break existing tests." <commentary> The issue-fixer focuses on a single issue, applies the fix, and verifies it works. </commentary> </example> <example> Context: Code review found missing error handling prompt: "Fix IMPORTANT issue: Unhandled promise rejection in api/fetch.ts:28. The async call has no try-catch." assistant: "I'll add proper error handling with try-catch, ensure errors are logged, and add appropriate user-facing error messages." <commentary> Agent handles the specific issue without over-engineering. </commentary> </example>
Executes a single task from a decomposed spec with the full implementation cycle: implement, test, review, and fix. Automatically updates STM status upon completion. <example> Context: Orchestrator needs to implement a specific task from a spec prompt: "Execute task [P1.3] from STM: Implement common hook utilities" assistant: "I'll load the task details from STM, implement the code, write tests, run code review, fix any critical issues, then mark the task complete." <commentary> The task-executor handles the complete lifecycle of a single task autonomously. </commentary> </example> <example> Context: A task needs implementation with testing prompt: "Execute task [P2.1]: Create user authentication module" assistant: "Loading task details... implementing auth module... writing tests... running review... all checks passed, marking task done." <commentary> Agent follows the full cycle and auto-updates STM status. </commentary> </example>
Battle-tested Claude Code plugin for engineering teams — 38 agents, 156 skills, 72 legacy command shims, production-ready hooks, and selective install workflows evolved through continuous real-world use
Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Comprehensive toolkit for developing Claude Code plugins. Includes 7 expert skills covering hooks, MCP integration, commands, agents, and best practices. AI-assisted plugin creation and validation.