Agent Skills: refactor
Code refactoring with AI assistance. Use for modernizing code, converting JavaScript to TypeScript, class to hooks conversions, and systematic renaming.
ID: johnlindquist/claude/refactor
267
Install this agent skill to your local
Skill Files
The files that make up refactor.
Loading file tree…
More agent skills
- agent-mailInter-agent communication for multi-agent workflows. Use when multiple agents need to coordinate, share information, or reserve resources.
- review-logging-patternsReview code for logging patterns and suggest evlog adoption. Optionally use @evlog/cli (`evlog init` to wire evlog, `evlog agents` to write the conventions into AGENTS.md, `evlog map` to score entry-point coverage, `--baseline` to gate regressions in CI) on Nuxt, Nitro, Next.js, TanStack Start, and Hono. Guides setup on those plus SvelteKit, React Router, NestJS, Express, Fastify, Elysia, oRPC, Cloudflare Workers, AWS Lambda, Astro, and standalone TypeScript. Detects console.log spam, unstructured errors, and missing context. Covers wide events, structured errors, drain adapters (Axiom, OTLP, HyperDX, PostHog, Sentry, Better Stack, Datadog, Loki, ClickHouse, NuxtHub, Memory), sampling, enrichers, and AI SDK integration.
- glycoengineeringAnalyze and engineer protein glycosylation. Scan sequences for N-glycosylation sequons (N-X-S/T), predict O-glycosylation hotspots, and access curated glycoengineering tools (NetOGlyc, GlycoShield, GlycoWorkbench). For glycoprotein engineering, therapeutic antibody optimization, and vaccine design.
- json-canvasCreate and edit JSON Canvas files (.canvas) with nodes, edges, groups, and connections. Use when working with .canvas files, creating visual canvases, mind maps, flowcharts, or when the user mentions Canvas files in Obsidian.
- pricing-strategyHelp users validate willingness-to-pay, select the right value metrics, and continuously optimize pricing and packaging to drive growth.
- hypothesis-generationFormulate evidence-bounded scientific questions, candidate hypotheses, rival explanations, causal or associational claims, discriminating predictions, measurements, and preregistration-ready analysis plans. Use when turning observations or preliminary findings into transparent, testable research plans without treating hypotheses as facts.