Evaluating Trade Offs logo

Evaluating Trade Offs

Community
cnfeat
evaluating-trade-offs

Help users make better decisions between competing options. Use when someone is weighing pros and cons, comparing alternatives, struggling with a difficult choice, deciding between speed and quality, or asking "should we do X or Y?"

Overview

Publishercnfeat
Repositorytop-pm-skills
Skill nameevaluating-trade-offs
Stars
55
Forks
6
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by cnfeat on GitHub. Read the source before you install it.

Installation

Install the Evaluating Trade Offs AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/cnfeat/top-pm-skills/tree/main/参考skill/lenny-skills-main%20(2)/lenny-skills-main/skills/evaluating-trade-offs
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Use it in TypingMind

Enable Evaluating Trade Offs in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Evaluating Trade Offs on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Evaluating Trade Offs is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Evaluating Trade-offs

Help the user make clearer decisions between competing options using frameworks and mental models from 40 product leaders.

How to Help

When the user asks for help evaluating trade-offs:

  1. Understand the decision context - Ask what they're optimizing for (short-term vs. long-term, growth vs. quality, speed vs. thoroughness) and what makes this decision difficult
  2. Identify the real constraints - Help distinguish between actual constraints and assumed ones. Ask "What would you do if [constraint] weren't an issue?"
  3. Surface hidden costs - Help quantify the full cost of each option, including maintenance burden, opportunity cost, and second-order effects
  4. Apply the right framework - Use weighted criteria matrices for complex multi-factor decisions, or simple "would I start this today?" tests for continuation decisions

Core Principles

Optimize for order-of-magnitude, not precision

Alex Komoroske: "It doesn't really matter if it's 1,000 or 1,001, who cares? It's orders of magnitude larger than the alternative, and so it is better." Don't waste effort on false precision in uncertain environments - focus on whether one option is dramatically better, not marginally better.

Apply the "would I start this today?" test

Annie Duke: "If you wouldn't start this today, then that means that everything that you're putting into this going forward is the actual waste." When evaluating whether to continue a project, ignore sunk costs entirely. The only relevant question is whether you'd begin this effort with today's knowledge.

Think more, ship better

Anuj Rathi: "Most experiments should be thought experiments. They should not even be tried out because they're obviously going to fail." Don't default to "let's just try it" - rigorous upfront thinking eliminates weak ideas before they consume engineering resources.

Accept "worse first" for long-term gains

Graham Weaver: "Everything you want is on the other side of worse first." Meaningful change requires accepting short-term decline. Ask what your 5-year future self would want, not what makes tomorrow easier.

Create decision tenets to eliminate recurring debates

Bob Baxley: "Tenets are really decision-making tools... you sort of make a rule for yourself." Identify debates your team has repeatedly and create a tenet to decide the direction once. Good tenets are specific enough that someone could reasonably argue the opposite.

Quantify countervailing metrics

Ronny Kohavi: "Here's the money that we generate from the emails. Here's the money that we're losing on long-term value. What's the trade-off?" Assign dollar values to negative user actions (unsubscribes, churn) to make objective trade-offs against short-term gains.

Use a weighted criteria matrix

Nicole Forsgren: "Identify the criteria that are most important to you... give everything a score, and just multiply it out." Create a decision-making spreadsheet with options as rows and weighted criteria as columns. The process often reveals the answer before the math is finished.

Present clear "either/or" choices to leadership

Geoff Charles: "Be very clear with the tradeoffs... present those tradeoffs back to your leadership team. Here's what we're doing and here's what we're not doing." Communicate what the team is NOT doing as clearly as what they are doing. Present a "menu" of options to force a decision.

Separate "can" from "should"

John Cutler: "Some people are just locked into the can. They're uber pragmatic... others ask 'What should we do here?'" Don't let feasibility constraints dominate strategic thinking. Explicitly ask what you should do if technical debt weren't an issue.

Diagnose with data, treat with design

Julie Zhuo: "Data is not a tool that's going to tell you what you should build... but it can tell you if you have a problem." Use data to identify problems and gaps, but rely on design and intuition to invent solutions.

Beware the cost of analysis itself

Stewart Butterfield: "The cost of doing the analysis was this much. So it's guaranteed to be a loser." Evaluate whether the person-hours spent analyzing a decision exceed the maximum possible upside of the improvement.

Identify who loses

Ramesh Johari: "Many of the changes that are most consequential create winners and losers." When launching a feature, explicitly identify who will lose and decide if the winners provide more net value to the ecosystem.

Questions to Help Users

  • "What are you optimizing for - today, this quarter, or this year?"
  • "If you weren't already committed to this, would you start it today?"
  • "What's the full 'all-in' cost of each option, including maintenance and opportunity cost?"
  • "Is this decision reversible or a one-way door?"
  • "Who loses if you choose option A? Is that trade-off acceptable?"
  • "What would your 5-year future self wish you had done?"

Common Mistakes to Flag

  • False precision - Spending excessive time distinguishing between options that are only marginally different when the real question is order-of-magnitude
  • Sunk cost fallacy - Continuing a failing path because of what's already been invested rather than evaluating future value
  • Analysis paralysis - When the cost of deciding exceeds the value difference between options
  • Ignoring second-order effects - Not accounting for maintenance burden, feature creep, or organizational complexity that comes after launch
  • Defaulting to your skillset - As Bret Taylor notes, "If you're a great engineer, the answer to almost every problem is engineering... you probably should question it"

Deep Dive

For all 42 insights from 40 guests, see references/guest-insights.md

Related Skills

  • Prioritizing Roadmap
  • Running Decision Processes
  • Scoping and Cutting
  • Managing Tech Debt

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Evaluating Trade Offs AI skill do?

Help users make better decisions between competing options. Use when someone is weighing pros and cons, comparing alternatives, struggling with a difficult choice, deciding between speed and quality, or asking "should we do X or Y?"

Why use Evaluating Trade Offs on TypingMind?

Because you install it once and use it with any model. Evaluating Trade Offs is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Evaluating Trade Offs in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cnfeat/top-pm-skills/tree/main/参考skill/lenny-skills-main%20(2)/lenny-skills-main/skills/evaluating-trade-offs. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Evaluating Trade Offs?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Evaluating Trade Offs?

As many as you like. As long as a model supports skills, you can use Evaluating Trade Offs with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Evaluating Trade Offs AI skill free?

Yes. It is published on GitHub by cnfeat under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇