claude-code-config-profiles

Audit and set up a codebase for agentic AI development using the 16-principle manifesto

Reviews code for architectural compliance and design integrity

Injects mistake-derived test requirements into the TDD pipeline

Clusters similar lessons and synthesizes testable patterns

Reviews UI code for design quality against the build-great-things quality checklist. Conditional — only activates when the Verification Contract includes design_craft_check evidence.

Analyzes repository structure, conventions, and patterns

Decompose a large system specification into cook-it-ready epic beads via DDD bounded contexts

Reflect on the cycle and capture high-quality lessons for future sessions

Full-cycle orchestrator chaining all five phases with gates and controls

Reference for configuring, launching, and monitoring infinity loops and polish loops

Decompose work into small testable tasks with clear dependencies

Hands-on QA testing of running applications via browser automation. Use whenever the user asks to test a running app, perform exploratory testing, verify UI/UX behavior, check accessibility, test forms and inputs, inspect network requests, do a smoke test, or systematically try to break things. Also use when review needs runtime verification beyond automated tests -- visual checks, boundary inputs, interaction flows, and design review against a live application. Triggers on phrases like "test this app", "QA this", "check the UI", "try to break it", "smoke test", "does this look right", "test the form", "check accessibility", "poke at it", or any request to manually verify a running web application or API.

Multi-agent review with lesson-calibrated reviewers, runtime verification, and severity classification

Develop precise specifications through Socratic dialogue, EARS notation, and Mermaid diagrams

Multi-phase test suite optimization with adversarial review

Team-based TDD execution with adaptive complexity and agent delegation

Load compound-agent workflow context after compaction or context loss

Audit and set up a codebase for agentic AI development using the 16-principle manifesto

Decompose a large system specification into cook-it-ready epic beads via DDD bounded contexts

Reflect on the cycle and capture high-quality lessons for future sessions

Full-cycle orchestrator chaining all five phases with gates and controls

Reference for configuring, launching, and monitoring infinity loops and polish loops

Decompose work into small testable tasks with clear dependencies

Multi-agent review with lesson-calibrated reviewers, runtime verification, and severity classification

Develop precise specifications through Socratic dialogue, EARS notation, and Mermaid diagrams

Team-based TDD execution with adaptive complexity and agent delegation