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Found 306 Skills
ReactLynx best practices covering dual-thread architecture and React patterns. Provides rules reference for writing, static analysis for reviewing, and auto-fix for refactoring.
Create a detailed refactor plan with tiny commits via user interview, then file it as a GitHub issue. Use when user wants to plan a refactor, create a refactoring RFC, or break a refactor into safe incremental steps.
Identify refactoring opportunities by surfacing architectural friction. Apply the deletion test, deep-modules vocabulary, and seams analysis. Each opportunity becomes its own evanflow-writing-plans cycle. Use when reviewing code for refactoring, when a file has grown too large, or when architecture concerns surface during feature work.
Vertical-slice TDD for any production code. One test → one impl → repeat. Tests verify behavior through public interfaces, not internals. Use when implementing any feature, bugfix, or behavior change.
Design a module's interface using parallel sub-agents producing radically different designs ("design it twice"). Compare on depth, simplicity, and efficiency. Embedded grill on the synthesized choice. Use when designing a new API, exploring interface options, or deciding the shape of a refactor before writing code.
Use this for {{FRAMEWORK}} components, pages, hooks, forms, and frontend refactors that should follow Panapps coding standards and review checklist.
Build a compilable type-level skeleton from a high-level architecture spec before writing any implementation logic. Use when you have an architectural assessment, design doc, or restructuring plan and need to prove the new architecture is sound before migrating code. Also use when asked to "scaffold the new architecture", "create type stubs", "build the shell", "flesh out this spec", "skeleton the modules", or any request to turn architectural intent into verified structure. This skill follows the "Human Builds the Shell" paradigm: types are hard constraints that the compiler enforces, so if the skeleton compiles, the architecture is structurally sound. Especially valuable for large refactors where you don't trust agents to maintain coherence.
[Hyper] Optimize an existing codebase through baseline-first experiments, binary evaluation, and one-mutation-at-a-time iteration. Use for codebase autoresearch, measured bottleneck reduction, benchmarked code optimization, and evidence-backed refactors.
Detect and simplify overly complex code. Apply KISS principle - less is more.
Expertise in Senior Principal Engineering refactoring. Use when you need to eliminate technical debt, remove "AI Slop," simplify complex logic, and ensure DRY code.
Modernize legacy codebases, migrate frameworks, and reduce technical debt. Use for legacy system updates or framework migrations.
Use the JetBrains IDE MCP Server (IntelliJ IDEA 2025.2+) to let an external client drive IDE-backed actions: run Run Configurations, execute commands in the IDE terminal, read/create/edit project files, search via IDE indexes (text/regex), retrieve code inspections for a file, fetch symbol info, perform rename refactoring, list modules/dependencies/repos, open files in the editor, and reformat code. Use when you want IDE-grade indexing/refactoring/inspection instead of raw shell scripting.