operations-advisor-qu

Analyzes growth decisions using Qu Hui's north star metric and experimentation frameworks.

187|12|Updated Jun 1, 2026
One-click install
npx skills add https://github.com/Luyu2026/Skill-Bible --skill operations-advisor-qu-luyu2026
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: operations-advisor-qu
Source: https://github.com/Luyu2026/Skill-Bible/tree/main/general-operations-skills/operations-advisor-qu
Command: npx skills add https://github.com/Luyu2026/Skill-Bible --skill operations-advisor-qu-luyu2026

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Operations and growth decisions often stall on judgment questions rather than execution: which metric to watch, whether an action is worth doing, and how to design a growth experiment. This Skill distills Qu Hui's growth-hacking frameworks (from "The Silicon Valley Growth Hacker's Field Notes") into callable mental models, decision heuristics, and anti-patterns so a data-driven growth perspective is available on demand. ## Core Features & Use Cases - North Star Metric Selection: Apply a 6-question filter to choose a single leading indicator that reflects user value and supports business goals. - Growth Model Decomposition: Break the north star metric into additive (channels/segments) and multiplicative (conversion rates) formulas to locate the weakest lever, using "pour fuel on fire" or "fix the leak" strategies. - Experiment Loop Design: Structure ideas through ICE prioritization, A/B testing, and scale-or-drop cycles with explicit honesty boundaries and source citations. - Use Case: Paste your current growth plan or metric dashboard and ask whether your chosen KPI is a vanity metric, which funnel stage to fix first, or how to design the next two-week experiment cycle. ## Quick Start Ask the agent to analyze your growth question, metric choice, or experiment plan using the operations-advisor-qu perspective.

Frequently Asked Questions about operations-advisor-qu

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I choose a north star metric for my product?▼

Apply the 6-question filter: does it reflect core user value, support business goals, reflect activity, point in a good direction, stay simple, and act as a leading rather than lagging indicator. Revisit the choice as strategy stages change, since the right metric evolves over time.

What is a growth model and how do I build one?▼

A growth model decomposes your north star metric into an additive (channels and segments) times multiplicative (conversion rates) formula. Define the north star, record user steps, then assemble the formula to locate the weakest lever worth fixing.

How should I prioritize growth experiments?▼

Run one-to-two-week experiment cycles: collect ideas, rank them with ICE scoring, A/B test on small traffic, then scale winners or drop losers. Experiment for learning rather than wins, and avoid scattered tests without prioritization or cadence.

When should I not invest in growth?▼

Do not start growth spending before product-market fit is validated, since growing a product without value accelerates failure. The framework also fits poorly for early cold-start stages and requires data infrastructure and engineering resources to run experiments.

What are vanity metrics and why avoid them?▼

Vanity metrics like downloads, follower counts, and raw clicks correlate weakly with user value and should not serve as north star metrics. Decisions based on lagging or vanity indicators surface problems only after they can no longer be corrected.