Results for “star”

Choose and audit startup metrics using the Lean Analytics framework: separate actionable metrics from vanity metrics, identify the One Metric That Matters for your business model and stage, set targets, and plan instrumentation.

Write a project charter that pins down goal, scope, success criteria, and stakeholders before work starts.

Use the skill-builder skill to start the interactive skill-creation workflow for $ARGUMENTS.

Start, stop, and query Play-In-Editor (PIE) sessions for runtime testing of Blueprints, gameplay logic, widgets, AI, and any in-game behavior. Use when the user asks you to "play", "test", "run", "PIE", "start/stop the game", or otherwise needs a live game world to validate changes.

Start an autonomous experiment loop with user-selected interval (10min, 1h, daily, weekly, monthly). Uses CronCreate for scheduling.

Start an autonomous experiment loop with user-selected interval (10min, 1h, daily, weekly, monthly). Uses CronCreate for scheduling.

Start an autonomous experiment loop with user-selected interval (10min, 1h, daily, weekly, monthly). Uses CronCreate for scheduling.

Get started with Naive UI - a Vue 3 component library with comprehensive installation and setup guide

Start an autonomous experiment loop with user-selected interval (10min, 1h, daily, weekly, monthly). Uses CronCreate for scheduling.

Onboard a new GTM project — run an agency-style interview, then generate CLAUDE.md, PROGRESS.md, about/me.md, strategy/brand.md, and scaffold content + assets folders. Use this skill whenever the user wants to set up a new project, onboard a brand, start from scratch, configure their marketing context, or initialize their workspace. Trigger on: bootstrap, onboard, set up my project, get started, configure my brand, initialize, new project setup, brand onboarding, set up my brand, create project structure, onboard my company, set up content folders, prepare my workspace, start a new GTM project. Also use when the user seems to be starting fresh and hasn't set up strategy/brand.md or about/me.md yet.

Startup skill router: maps any incoming request to the correct skill using Quick Lookup table and _manifest.json. Loaded automatically at session start. Triggers on: every new request — this is the dispatch layer, not a user-facing skill. NOT for: executing tasks directly — always routes to a domain-specific skill.

Model cap tables, dilution scenarios, and vesting schedules for startups. Use when planning fundraising, pricing options, or tracking equity.

Introduction to literature search & review skills - systematic paper finding, screening, extraction, and citation traversal

Interactive project setup wizard. From a clean codebase, guides user through provider selection (OpenAI/Azure/DeepSeek/Ollama/Qwen/Gemini/etc.), API key configuration, dependency installation, config generation, and launches the dashboard. If user selects an unimplemented provider, auto-scaffolds the provider code following the plugin architecture. Auto-diagnoses and fixes startup failures with up to 3 retry rounds. Use when user says 'setup', 'set up', 'configure', 'init project', '初始化', '环境配置', '项目配置', 'first run', 'get started', 'quick start', or wants to configure and launch the project from scratch.

Interactive project setup wizard. From a clean codebase, guides user through provider selection (OpenAI/Azure/DeepSeek/Ollama/Qwen/Gemini/etc.), API key configuration, dependency installation, config generation, and launches the dashboard. If user selects an unimplemented provider, auto-scaffolds the provider code following the plugin architecture. Auto-diagnoses and fixes startup failures with up to 3 retry rounds. Use when user says 'setup', 'set up', 'configure', 'init project', '初始化', '环境配置', '项目配置', 'first run', 'get started', 'quick start', or wants to configure and launch the project from scratch.

Interactive project setup wizard. From a clean codebase, guides user through provider selection (OpenAI/Azure/DeepSeek/Ollama/Qwen/Gemini/etc.), API key configuration, dependency installation, config generation, and launches the dashboard. If user selects an unimplemented provider, auto-scaffolds the provider code following the plugin architecture. Auto-diagnoses and fixes startup failures with up to 3 retry rounds. Use when user says 'setup', 'set up', 'configure', 'init project', '初始化', '环境配置', '项目配置', 'first run', 'get started', 'quick start', or wants to configure and launch the project from scratch.

Simulator.Company environment setup specialist. Use when the user wants to connect to Simulator.Company, set up credentials, authenticate, configure the workspace, or start working with Simulator for the first time. Activate when the user says "init", "setup", "connect to simulator", "login to simulator", "configure simulator", "get started with simulator", or "set workspace".

Design or improve onboarding flows, empty states, and first-time user experiences. Helps users get started successfully and understand value quickly.

Design or improve onboarding flows, empty states, and first-time user experiences. Helps users get started successfully and understand value quickly.

Autopsy a stuck project, extract salvageable artifacts, and route to a fresh start via $bootstrap-repo reset or new-repo bootstrap

Use when starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying questions

Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.

Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.

Use when aligning spliced RNA-seq reads to a reference genome, generating genome indices, or performing splice-aware alignment for transcriptome analysis.

Serverless computing patterns. AWS Lambda, Azure Functions, GCP Cloud Functions. Deployment frameworks: Serverless Framework, AWS SAM, SST. Cold starts, event sources, and production optimization. USE WHEN: user mentions "serverless", "Lambda", "cloud function", "Azure Functions", "SAM", "SST", "Serverless Framework", "cold start", "FaaS" DO NOT USE FOR: container orchestration - use `kubernetes` or `docker`; always-on servers - use backend framework skills

Validate a business idea using the minimalist entrepreneur framework before building anything.

Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions

Use before any creative or ambiguous work - new features, new components, or behavior changes - to explore intent, requirements, and design before implementation starts.

Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions

ade-ops setup — START HERE on a fresh clone. Scenario-aware onboarding for Databricks with Power BI and/or Microsoft Fabric.

GitHub 이슈 번호를 받아 본문·코멘트·첨부 이미지를 gh로 수집해 실제로 읽고, 프론트엔드/백엔드 성격에 맞춰 코드베이스와 대조 분석해 계획을 세운 뒤, 워크트리를 만들어 구현하고 커밋하고, 전후 증거를 webp 로 캡처해 기본 브랜치에 먼저 커밋한 다음 이슈에 렌더링되는 리포트를 남깁니다. 이슈 번호 대신 작업 설명을 주면 issue-create 로 이슈부터 등록합니다. `$issue-start`, "이슈 착수", "이슈 분석하고 작업해줘" 요청에 사용합니다.

Product Hunt launch optimization with specific specs, timing, and gallery strategy. Covers taglines, gallery images, maker comments, and launch day tactics. Use for: product launches, startup launches, side project launches, Product Hunt optimization. Triggers: product hunt, ph launch, product hunt launch, launch strategy, product launch, startup launch, product hunt tips, product hunt gallery, ph optimization, launch day, product hunt maker

Brainstorm an inspiring, achievable, and emotional product vision that motivates teams and aligns stakeholders.

Creates isolated git worktrees with smart directory selection and safety verification before starting feature work.

Run multi-agent research discourse session. Use when the user requests to "start a research party" or "run a journal club".

How you ask the model matters more than which model you ask. Two disciplines stop most AI coding failures before they start.