GSD

Analyzes codebases and generates structured documentation for various focus areas.

Creates executable phase plans with task breakdown and dependency analysis.

Executes GSD plans with atomic commits and deviation handling.

Researches gray area decisions and provides structured comparison tables.

Researches business domain context for AI systems, identifying evaluation criteria and failure modes.

Automates the research of AI frameworks to deliver implementation-ready guidance and best practices.

Automates the writing and updating of project documentation based on specific assignments.

Audits code against threat mitigations in PLAN.md, producing a detailed SECURITY.md report.

Manages multi-cycle debugging sessions, ensuring efficient checkpoint handling and agent spawning.

Verifies phase goal achievement through goal-backward analysis, ensuring codebase aligns with promised outcomes.

Generates UI-SPEC.md design contracts for frontend phases based on upstream artifacts.

Classifies planning documents into categories like ADR, PRD, SPEC, or DOC, ensuring accurate extraction of information.

Interactive decision matrix for selecting the right AI/LLM framework based on user needs.

Verifies cross-phase integration and end-to-end workflows in applications.

Analyzes codebases and generates structured intelligence files for project insights.

Analyzes codebase patterns and generates a mapping file for new files.

Researches domain ecosystems to inform project roadmaps.

Analyzes developer session messages to create a detailed behavioral profile across 8 dimensions.

A powerful collection of tools for efficient AI-driven development and context management.

Validates UI-SPEC.md design contracts against quality dimensions to ensure design integrity.

Consolidates classified planning documents into a unified context while managing conflicts.

Verifies phase plans will achieve their goals before execution through goal-backward analysis.

Automated code reviewer that identifies bugs, security issues, and code quality problems.

Creates detailed project roadmaps by mapping requirements to phases with clear success criteria.

Conducts a retroactive audit of AI evaluation coverage against planned strategies.

Automate bug investigation using a scientific approach and manage debug sessions effectively.

Conducts a thorough visual audit of frontend code against design standards, producing actionable insights.

Automates code fixes based on review findings, ensuring intelligent and atomic updates.

Generates tests to fill Nyquist validation gaps and verifies coverage for phase requirements.

Analyzes codebases to extract structured assumptions for specific phases.

Synthesizes research outputs from multiple agents into a cohesive summary for roadmap creation.

Designs structured evaluation strategies for AI phases, ensuring robust assessment and monitoring.

Researches pre-planning phases and produces structured documentation for planners.