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galz10
Refactors code to eliminate technical debt, remove redundant AI-generated code, simplify logic, and enforce DRY principles.
galz10
Manages Linear project tickets locally using Markdown, enabling creation, updates, searches, and atomic task breakdown.
galz10
Reviews technical research for objectivity, evidence, and completeness to meet the Documentarian standard.
galz10
Conducts technical research to understand codebases, trace data flows, and map implementation patterns for effective code navigation and analysis.
galz10
Executes technical plans via code implementation, rigorous testing, and iterative verification to ensure high-quality output without unnecessary steps.
galz10
Activates the Pickle Rick persona mode in response to explicit user requests, providing a themed conversational experience.
galz10
Reviews implementation plans for architectural soundness, specificity, and safety to prevent vague plans and messy code before development begins.
galz10
Drafts comprehensive Product Requirements Documents (PRDs) to define feature scope, goals, and requirements prior to development.
galz10
Creates detailed, atomic, and safe step-by-step technical implementation plans from requirements to guide development execution.
MadAppGang
Tracks and analyzes agent, skill, and model performance metrics including success rates, latency, and cost for AI system optimization.
MadAppGang
Provides standardized architectural patterns and templates for building consistent Claude Code plugins, ensuring uniform structure and design across development.
MadAppGang
Provides on-demand analysis to identify performance bottlenecks, reduce build times, and optimize code for better efficiency.
MadAppGang
Coordinates multiple AI agents in parallel or sequential workflows, enabling delegation, task decomposition, and dynamic agent switching for complex task execution.
MadAppGang
Analyzes UI visual patterns using Gemini AI for design insights, including provider detection and severity assessment.
MadAppGang
Optimizes workflow speed by batching related operations into single messages, enabling parallel execution and eliminating sequential bottlenecks.
MadAppGang
Reference guide for PROXY_MODE configuration with external AI models, including routing prefixes for MiniMax, Kimi, and GLM APIs to enable multi-model integration and debugging.
MadAppGang
Generates and manages Architecture Decision Records (ADRs) to document technical trade-offs, architectural choices, and decision logs for software projects.
MadAppGang
Validates agent outputs against original objectives at checkpoints to prevent goal drift in complex multi-agent workflows.
MadAppGang
Provides UI implementation patterns based on design analysis, incorporating Anti-AI design rules and visual verification for improved user interfaces.
MadAppGang
Provides YAML format for defining Claude Code agents, offering an alternative to markdown for agent creation, conversion, and schema validation.
MadAppGang
Enables implementation of quality gates, user feedback loops, and test-driven development for iterative software validation and issue classification.
MadAppGang
Automates tracking and visibility for multi-phase workflows, managing iterations and parallel tasks in real-time.
MadAppGang
Performs on-demand security and code quality audits to identify vulnerabilities, security issues, and compliance problems.
MadAppGang
Standardizes MCP server implementation, tool interfaces, and naming conventions for Claude Code plugins to ensure consistent plugin development.