58건 · 관련도순
Create presentation slides with scripts for each page and a separate teleprompter window. View current and next slides, script text, and a timer, with keyboard controls for switching among five visual themes.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Operating SOP for DSPy (Stanford NLP) — the declarative framework for "programming, not prompting" language models. Activate when the user says any of: "use DSPy", "compile a prompt", "optimize prompts/programs", "MIPRO/MIPROv2", "BootstrapFewShot", "GEPA", "Signatures + Modules", "teleprompter", "auto-tune prompts for a different LM", or whenever a brittle hand-crafted prompt pipeline needs to be turned into a *compiled*, measurable, swappable program. Do NOT activate for one-shot prompt tweaks, no-metric exploratory work, or pipelines where prompts must remain human-authored verbatim — use raw prompting or LangChain templates instead.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
ENHANCE overlay on [[dspy]] — the upfront rubric for choosing a reasoning SHAPE (Predict / ChainOfThought / ReAct / ProgramOfThought) BEFORE you write a prompt or pick an optimizer. The local `dspy` skill lists the modules but never surfaces the *selection criterion*: reasoning shape is chosen by task structure, not by reflexively defaulting to CoT. Activate every time a new LM-calling node/step is added to a pipeline. Do NOT activate for one-shot prompts, optimizer/teleprompter choice (that is the dspy SOP's job), or non-LM control flow. Search keywords: chain of thought vs ReAct, when to use CoT, reasoning type, ReAct vs CoT vs PoT, which dspy module, predict vs chain of thought.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
DSPy is a Python framework from Stanford NLP that replaces hand-written prompts with code: you declare LLM tasks as typed signatures, compose them into modules, and let optimizers (BootstrapFewShot, MIPROv2, GEPA) tune the prompts and few-shot examples against your metric. Use when the user asks about DSPy, signatures, ChainOfThought, ReAct, teleprompters or optimizers, or wants to stop hand-tuning prompts.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Writing style guide for technical content, social media, blog posts, READMEs, git commits, and developer documentation. Optimized to avoid AI detection patterns. Use when writing any content beyond code.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Set up and configure WorkOS AuthKit authentication with Convex backend. Use when integrating AuthKit, configuring JWT providers, setting up environment variables, or implementing sign in and sign out flows with React and Vite. Supports Netlify deployment.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Debug and troubleshoot WorkOS AuthKit authentication issues with Convex. Use when authentication fails, JWT validation errors occur, user identity returns null, email claims are missing, admin access checks fail, or sign in button does not work. Supports Netlify deployment.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when deploying this teleprompt app with get-convex/static-hosting, especially when the user says /deploydev, /deployprod, deploy dev, deploy prod, deploy production, upload static hosting, or asks which Convex static-hosting command to run. Keeps dev uploads on fearless-dolphin-422 and production uploads on befitting-dodo-95.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Designs and improves onboarding flows, empty states, and first-run experiences to help users reach value quickly. Use when the user mentions onboarding, first-time users, empty states, activation, getting started, or new user flows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Add moments of joy, personality, and unexpected touches that make interfaces memorable and enjoyable to use. Elevates functional to delightful. Use when the user asks to add polish, personality, animations, micro-interactions, delight, or make an interface feel fun or memorable.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Performs a final quality pass fixing alignment, spacing, consistency, and micro-detail issues before shipping. Use when the user mentions polish, finishing touches, pre-launch review, something looks off, or wants to go from good to great.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Routes general Convex requests to the right project skill. Use when the user asks which Convex skill to use or gives an underspecified Convex app task.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Integrate Convex static self hosting into existing apps using the latest upstream instructions from get-convex/self-hosting every time. Use when setting up upload APIs, HTTP routes, deployment scripts, migration from external hosting, or troubleshooting static deploy issues across React, Vite, Next.js, and other frontends.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Patterns for scaling read-heavy Convex apps to millions of users. Use when optimizing bandwidth, reducing query costs, fixing slow queries, creating digest tables, replacing reactive subscriptions with one-shot fetches, adding compound indexes, debouncing writes, rate-controlling backfills, or running npx convex insights. Trigger when users mention "scale", "bandwidth", "performance", "optimize", "slow queries", "expensive queries", "digest table", "denormalize", or "thundering herd" in the context of Convex.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Create Convex queries, mutations, and actions with proper validation, authentication, and error handling. Use when implementing new API endpoints.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when the user says /deploydev, deploy dev, upload dev static hosting, or asks to deploy the current app to its development Convex static-hosting target.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Amplify safe or boring designs to make them more visually interesting and stimulating. Increases impact while maintaining usability. Use when the user says the design looks bland, generic, too safe, lacks personality, or wants more visual impact and character.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Reflection-first problem solving methodology for Convex development. Use before implementing any solution to ensure proper root cause analysis, 98% code confidence, and minimal change scope.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert Convex Auth setup, production, OAuth, security, and debugging guidance. Use when adding or auditing Convex Auth, configuring GitHub/Google/Apple OAuth, setting auth env vars, protecting Convex functions with getAuthUserId, debugging callback URLs, preparing production auth, rotating keys, or reviewing auth security.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality review.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Improve layout, spacing, and visual rhythm. Fixes monotonous grids, inconsistent spacing, and weak visual hierarchy. Use when the user mentions layout feeling off, spacing issues, visual hierarchy, crowded UI, alignment problems, or wanting better composition.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when the user says /localstop, localstop, stop localhost for this app, /localstopall, localstopall, or asks to stop local development servers for this Teleprompt app.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Audits Convex performance for reads, subscriptions, write contention, and function limits. Use for slow features, insights findings, OCC conflicts, or read amplification.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Guide for when to use and when not to use return validators in Convex functions. Use this skill whenever the user is writing Convex queries, mutations, or actions and needs guidance on return value validation. Also trigger when the user asks about Convex type safety, runtime validation, AI-generated Convex code, Convex AI rules, Convex security best practices, or when they're debugging return type issues in Convex functions. Trigger this skill when users mention "validators", "returns", "return type", or "exact types" in the context of Convex development. Also trigger when writing or reviewing Convex AI rules or prompts that instruct LLMs how to write Convex code.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.