Loading...
Loading...
Found 5,470 Skills
Re-run production readiness assessment and compare against previous results. Use when the user has fixed issues and wants to see their progress — shows before/after scores and what improved.
Use when implementing features, writing fullstack code, shipping UI + API + DB changes, or any hands-on engineering work in TypeScript, Python, React, Next.js, FastAPI, or SQL
Interact with the learning system: show stats, list/search accumulated knowledge, and graduate mature entries into agents/skills. Backed by learning.db (SQLite + FTS5). Use when user says "retro", "retro list", "retro search", "retro graduate", "check knowledge", "what have we learned", "knowledge health", "graduate knowledge".
Persistent markdown files as working memory for complex tasks: plan, track progress, store findings. Use when tasks have 3+ phases, require research, span many tool calls, or risk context drift. Use for "plan", "break down", "track progress", "multi-step", or complex tasks. Do NOT use for simple lookups, single-file edits, or questions answerable in one response.
Personalized setup and onboarding wizard. Use when setting up OrchestKit for a new project, configuring plugins, or generating a readiness score and improvement plan.
TanStack Router bundler plugin for route generation and automatic code splitting. Supports Vite, Webpack, Rspack, and esbuild. Configures autoCodeSplitting, routesDirectory, target framework, and code split groupings.
Structured web research framework for AI agents. Teaches your agent to conduct multi-source research, synthesize findings into actionable briefs, maintain a research library, and track evolving topics over time. Use when you need market research, competitor analysis, topic deep-dives, or ongoing monitoring of trends and news. Works with any agent that has web search capabilities.
Profile and optimize application performance including load times, memory usage, and rendering. Use when debugging slow performance, memory leaks, or optimizing app speed.
Decomposes complex, multi-day tasks into optimized milestones using parallel reviewer agents (ultraplan). Spawns 5 independent reviewers that analyze the problem from different angles, then synthesizes their findings into a milestone dependency DAG. Triggers when the user says "plan milestones", "break this into milestones", "ultraplan", or when long-run harness needs milestone generation.
Use when needing to set optimal prices for products or services, maximize profit while maintaining competitiveness, and design pricing tiers
Use this when you have specifications or requirements for multi-step tasks, before starting to write code
Use this before claiming work is complete, fixed, or tested—before committing or creating a PR—you must run validation commands and confirm the output before claiming success; always back up assertions with evidence