Results for “mvp-planning”

当需要为某个生活领域或项目确立一个初步的、可迭代的积极方向时

Generate Minervini-style breakout trade plans from VCP screener output with risk calculation, portfolio heat management, and Alpaca-compatible order templates.

Mvp Pressure Launch

ML pipeline design — data versioning, experiment tracking, deployment patterns, drift monitoring. Use when building an ML pipeline from data to deployment, setting up MLOps tooling (DVC, MLflow, model registry), choosing deployment patterns (shadow, canary, A/B), or designing monitoring for drift and degradation.

Design user journeys and task flows for a product concept or MVP. Use when the team needs primary flows, branch conditions, edge cases, onboarding paths, and end-to-end user movement before screen planning or UI implementation.

Prioritize features for an MVP or first release. Use when the team has too many ideas and needs must-have vs later vs never-for-v1 decisions tied to the core value loop, user pain, operational shortcuts, and launch feasibility.

Guide building a minimum viable product through manual-first, then processized, then productized stages. Use when someone is ready to build their first product or struggling with scope.

Provides practical guidance for training Mixture-of-Experts Vision-Language Models in Megatron Bridge, comparing FSDP and 3D-parallel approaches with lessons from recent multimodal experiments.

当需要将个人技能或兴趣快速转化为可收费的咨询服务或自由职业服务时

Write an implementation plan from an approved architecture and MVP scope. Use when the team needs milestones, workstreams, dependency ordering, acceptance criteria, and execution sequencing that connect product intent to shippable engineering work.

Guide building a minimum viable product the minimalist entrepreneur way — manual first, then processized, then productized. Use when someone is ready to build their first product or struggling with scope.

Guides the creation of high-quality MCP servers that enable LLMs to interact with external services through well-designed tools, covering planning, implementation, and refinement for Python or Node/TypeScript.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

When the user needs a comprehensive marketing plan for a client, a company they advise, or their own product. Also use when the user mentions "marketing plan," "growth plan," "GTM plan," "go-to-market plan," "AARRR plan," "90-day marketing plan," "12-month marketing roadmap," "fractional CMO plan," or "fCMO plan." Generates an exhaustive 13-section plan structured by AARRR (Acquisition, Activation, Retention, Referral, Revenue), customized to the client's current budget, team, and stage, mapped to future funding milestones, cross-referenced with the 139-idea marketing-ideas library and an embedded 17-section current-state audit rubric, with a full marketing operations stack showing which skills and MCP/API integrations execute each part. Outputs a Notion-paste-ready markdown document. For positioning and ICP context before planning, see product-marketing. For stage-specific deep work, see onboarding, signup, emails, referrals, pricing.

Use when building a minimum viable product with maximum constraints

MCP (Model Context Protocol) server building principles.

Finetunes the NV-Generate-CTMR MR-brain diffusion UNet from user-supplied NIfTI training volumes using a wrapper that stages configs and delegates to upstream scripts.

Generate comprehensive rollout plans with preflight checks, step-by-step deployment, verification signals, rollback procedures, and communication plans for infrastructure and application changes.

Add Adaptive Card response templates to MCP-based API plugins for visual data presentation in Microsoft 365 Copilot.

Guides the creation of high-quality MCP servers that enable LLMs to interact with external services through well-designed tools, covering planning, implementation, testing, and evaluation.

Create and manage budgets with variance analysis and departmental allocation. Use when the user requests budget planning or provides relevant inputs for this workflow.

Production machine-learning engineering workflow for data contracts, reproducible training, model evaluation, deployment, monitoring, and rollback. Use when building, reviewing, or hardening ML systems beyond one-off notebooks.

Design an application database schema from product flows and backend responsibilities. Use when the team needs core entities, relationships, lifecycle fields, indexes, audit needs, tenancy boundaries, and migration-minded schema planning for an MVP or production system.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

When the user wants to create, optimize, or analyze a referral program, affiliate program, or word-of-mouth strategy. Also use when the user mentions 'referral,' 'affiliate,' 'ambassador,' 'word of mouth,' 'viral loop,' 'refer a friend,' or 'partner program.' This skill covers program design, incentive structure, and growth optimization.

Guides the creation of high-quality MCP servers that let LLMs interact with external services through well-designed tools, covering planning, implementation, testing, and evaluation.

Create performance improvement plan templates. TRIGGERS - Use when user needs help with pip-template related tasks.

Use when the team needs pricing, packaging, free-tier, trial, usage metering, or business-model guidance for a software product. Trigger on requests to design how the product should make money or control value access.

Design and optimize revenue operations systems that connect marketing, sales, and customer success into a unified revenue engine.

Analyze engineering delivery throughput, hiring funnel health, team structure, and production discipline for startup VPEs and founders.

Create a detailed, step-by-step implementation plan for a feature or project. Load when the user asks to plan a feature, create a technical roadmap, break down a PRD into tasks, design an implementation strategy, or sequence engineering work. Also triggers on "how should we build this", "implementation plan for", "technical breakdown", "task list for", or any request to turn a high-level requirement into a concrete execution plan. Supports phased rollouts, architecture-first, and MVP-focused planning.