Results for “product”

Provides production-grade NestJS architecture patterns for modules, controllers, providers, DTO validation, guards, interceptors, config, and testing.

Design and optimize email sequences, drip campaigns, and lifecycle automations for marketing and product teams.

Build production RAG pipelines and persistent agent memory using Pinecone as the vector database backend.

Generate a complete, production-ready MCP server project in TypeScript with tools, resources, and proper configuration.

Perform efficient pandas DataFrame operations for data analysis, manipulation, and transformation with production-grade patterns.

Calculate TAM, SAM, and SOM with explicit assumptions, methods, and caveats for market sizing.

Design the structure, hierarchy, and navigation model for a product's content and features.

Generates playful 8-character promotional slogans made of two four-character phrases, using internet slang for market stalls or product announcements.

Runs a structured five-round brainstorm to capture actors, features, scope, constraints, and business rules before writing a spec.

Provides MySQL and MariaDB schema, query, indexing, transaction, replication, and connection-pool patterns for production backends.

Transforms rough sketches or text descriptions into photorealistic 3D renders using Vizcom's AI rendering modes and prompt weighting.

Provides domain-specific knowledge for working with Remotion, covering 3D, animations, assets, audio, captions, and more.

Guides a structured interview and codebase exploration to produce a PRD, then submits it as a GitHub issue.

Selects and scores marketing ideas for SaaS products using a feasibility scoring system to prioritize high-impact, low-effort opportunities.

Never test mock behavior. Never add test-only methods to production classes. Understand dependencies before mocking. Language-agnostic principles with TypeScript/Jest and Python/pytest examples.

Guides through mocha test setup with step-by-step instructions, best practices, and production-ready configurations.

A rating component for collecting user feedback with customizable icons, colors, and half-star support in Naive UI. Ideal for product reviews, feedback forms, and rating systems.

Master Python 3.12+ with modern features, async programming, performance optimization, and production-ready practices. Expert in the latest Python ecosystem including uv, ruff, pydantic, and FastAPI.

Production-grade accessibility skill for WCAG 2.2 AA compliance. Covers auditing, remediation, component authoring, and validation workflows. Auto-invoked for UI implementation, a11y fixes, and accessibility testing.

Build production-ready LLM applications, RAG systems, and intelligent agents with architecture design, model selection, and cost controls.

Create production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling. Use when building new FastAPI applications or setting up backend API projects.

Perform a detailed SWOT analysis — strengths, weaknesses, opportunities, and threats with actionable recommendations. Use when doing strategic assessment, competitive analysis, or evaluating a product or business position.

Generate 5 creative, cost-effective marketing ideas with channels, messaging, and engagement rationale. Use when brainstorming marketing campaigns, planning product promotion, or looking for creative marketing tactics.

Visual UI review, browser-based design QA, and product-effectiveness critique for Nick's apps using Chromium/Playwright. Use when reviewing a live page or deploy to judge not just visual polish, but whether the interface supports clarity, trust, activation, conversion, responsiveness, and the product's strategic wedge. Best used after build/deploy to push a UI from acceptable to excellent with evidence from screenshots and browser inspection.

Comprehensive post-build verification of Shannon Framework's application outputs using three-layer methodology: Flow Verification (execution trace analysis), Artifact Verification (physical output inspection), and Functional Verification (runtime testing). Verifies Shannon built production-ready applications across all domains (Frontend, Backend, Database, Mobile, DevOps). Ensures NO MOCKS compliance, cross-platform functionality, and complete integration. Use after: Shannon builds any application via /shannon:wave, need to verify build quality, production readiness assessment.

Design, tune, and evaluate production RAG pipelines with deterministic tools for chunking, pipeline design, and retrieval evaluation.

Evaluate, design, and launch free tools for lead generation, SEO value, and brand awareness.

Transforms vague ideas into structured, actionable concepts through guided divergent and convergent thinking, producing a markdown one-pager.

Generate three alternative OKR sets for a team, aligned with company strategy, to spark strategic discussion and planning.

Transform output-focused roadmaps into outcome-focused ones that communicate strategic intent, rewriting initiatives as outcome statements reflecting user and business impacts.

Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights.

Brainstorm 3-5 monetization strategies with audience fit, risks, and validation experiments for a product or feature.

Plan and create lead magnets that capture emails, generate qualified leads, and drive product adoption.

Set up, improve, or audit analytics tracking and measurement for marketing and product decisions.

Generate production-quality Python scripts for FreeCAD CAD application, covering geometry creation, parametric objects, GUI tools, and automation.

Generate a complete, production-ready MCP server project in Ruby using the official MCP Ruby SDK.