
from my-cc-harness122
Practical performance and bundle-size guidelines for React and Next.js apps — prioritized rules and patterns to avoid common performance pitfalls.
Provides a concise, prioritized rulebook for React and Next.js performance: eliminating waterfalls, reducing bundle size, server-side and client-side performance patterns, and rendering/re-render strategies. The skill summarizes rules and points to individual rule files with examples.
Apply during code reviews, refactors, or when authoring React/Next.js components and pages where performance, bundle size, or server rendering behaviour matters. Triggers when optimizing data fetching, bundling, hydration, or re-render hotspots.
rules/ files in the repo with detailed examples (has_references=false per fetch metadata but sibling rules exists)async-parallel, bundle-dynamic-imports, rerender-memo) with guidance for application.Useful with developer-focused assistants and code-writing agents (Copilot-style, Claude/GPT code assistants) that can read rule files and apply transformations or generate code suggestions.
This skill has not been reviewed by our automated audit pipeline yet.
Harness Health Audit
Assess and score the overall health of a Claude Code harness across architecture, skills coverage, hooks, rules, MCP servers, eval pipelines, and team setup.
Code Evaluation Harness
Spawns an independent evaluator agent to score code outputs on functionality, code quality, originality, and usability/security, producing a structured EVAL_REP
SPEC-driven Development Interview
Conducts a structured, in-depth interview to produce a detailed SPEC.md requirements document for a feature or project.
Test-Driven Development (TDD)
Guides an agent through the TDD cycle: write a failing test, implement minimal code to pass, then refactor. Useful for disciplined feature development and maint
Plan
Create structured implementation plans for multi-step or architectural changes before coding — defines success criteria, trade-offs, and stepwise tasks.
Codex + Claude Code Review
Performs a dual-pass code review of the current branch using Codex (GPT) and Claude, producing structured findings and severity classifications.