Business & Operations

Use when implementation is complete, all tests pass, and you need to decide how to integrate the work

Use when you have a written implementation plan to execute in a separate session with review checkpoints

Turn-1 discovery question form for ambiguous briefs.

AI creative director with recursive self-assessment: 20+ methodologies (SIT, TRIZ, Bisociation, SCAMPER, Synectics), 3-axis evaluation calibrated against Cannes/D&AD/HumanKind, 5-phase process from brief to presentation.

Create a refreshable live operations artifact for customer success, support, or launch review workflows.

Hyperframes-based video template for retro pixel deck motion design. Use when users want a high-fidelity, multi-scene HTML-to-video composition with advanced transitions, interactive preview controls, and ready-to-render default style.

Generate boilerplate for a new statistic following library conventions

Run before/after benchmarks comparing current branch against master

Convert tasks from tasks.md into GitHub issues. Use after task breakdown

Break down implementation plans into actionable task lists. Use after

Convert tasks from tasks.md into GitHub issues. Use after task breakdown

Break down implementation plans into actionable task lists. Use after

Convert tasks from tasks.md into GitHub issues. Use after task breakdown

Break down implementation plans into actionable task lists. Use after

Execute the implementation planning workflow using the plan template to generate design artifacts.

Convert tasks from tasks.md into GitHub issues. Use after task breakdown

Break down implementation plans into actionable task lists. Use after

Transforms user prompts into optimized prompts using frameworks (RTF, RISEN, Chain of Thought, RODES, Chain of Density, RACE, RISE, STAR, SOAP, CLEAR, GROW)

You're a context engineering specialist who has optimized LLM applications handling millions of conversations. You've seen systems hit token limits, suffer context rot, and lose critical information mid-dialogue.

Language models exhibit predictable degradation patterns as context length increases. Understanding these patterns is essential for diagnosing failures and designing resilient systems.

Use when the user wants a quality review, interaction audit, or to test the workflow against realistic scenarios.

Use when the user wants to find problems, audit workflow quality, or get a comprehensive health check on their AI workflow.

Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.

Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.