Scope Cutter logo

Scope Cutter

Community
ojiudezue
scope-cutter

Use when the user is deciding what to cut from an onboarding flow, MVP scope, or feature list. Triggers on phrases like "cut scope", "what should we cut", "required vs optional", "progressive disclosure", "trim onboarding", "what's blocking activation", "the onboarding is too long". Implements the Required-vs-Helpful scope-cutting heuristics from Ch 3 and Ch 4 of Building Rocketships.

Overview

Publisherojiudezue
Repositoryproductmind-skills
Skill namescope-cutter
Stars
81
Forks
18
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Scope Cutter 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/ojiudezue/productmind-skills/tree/main/skills/scope-cutter
  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.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ojiudezue/productmind-skills.git /tmp/productmind-skills
mkdir -p .claude/skills
cp -r /tmp/productmind-skills/skills/scope-cutter .claude/skills/scope-cutter
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Scope Cutter 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 Scope Cutter 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 Scope Cutter 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.

Scope Cutter

What this does

Runs Ch 3/4's Required-vs-Helpful scope cutting on an onboarding flow or feature list. Returns a two-column allocation (Required vs Helpful) with rationale per item, plus the progressive-disclosure nudge sequence for everything that gets moved to Helpful. Targets the book's rule: cut the required-onboarding list in half.

When to use

Trigger when the user:

  • Has an onboarding flow with more than 4–5 required steps
  • Is shipping an SLC and needs to narrow scope (pairs with slc-or-mvp)
  • Has a "required fields" list on a form longer than feels reasonable
  • Is debating whether a feature belongs in v1 or v2
  • Has measured activation drop-off concentrated in onboarding

When NOT to use

  • The user is asking about the aha moment itself — that's aha-mapper, which feeds this skill its definition of "required"
  • The user is asking about tier feature segmentation (free vs paid) — that's reverse-freemium-design
  • There IS no current scope to cut — this skill prunes, it doesn't generate; run aha-mapper first if no loop is defined

The decision rule (from Ch 3/4)

For every item in the current required-onboarding list, ask:

If I removed this, would the user still hit the aha moment?

  • Yes (they'd still hit it): the item is Helpful, not Required. Move it out of the activation flow. Surface it later via progressive disclosure — empty-state nudge, contextual tooltip, dismissible banner after the first aha.
  • No (removing it blocks the aha): the item is Required. Keep in onboarding, but verify it's the minimum version (one calendar not five, one event type not multiple).

The book's stronger heuristic: cut the required list in half. Most PMs over-estimate what's required because every team owner argues their thing belongs in the flow. Forcing a 50% cut surfaces what is actually load-bearing.

Progressive disclosure for Helpful items

Each item moved to Helpful needs a re-introduction plan, not just deletion:

  1. First-aha trigger — nudge appears right after the user completes the smallest loop once
  2. Contextual surface — the nudge fires at the moment the user would benefit (when they create their second event type, prompt for default settings)
  3. Dismissible — user can skip and the nudge doesn't reappear for that session
  4. Maximum 3 nudges per session — beyond this is harassment

Items the user never taps after 5 sessions are candidates for the "Surface only on user request" bucket (a settings menu, not a proactive prompt).

Refusal mode

If the user insists on keeping the full required list ("but every step is important"), refuse to recommend the unchanged list and quantify the cost: each additional required step costs roughly 5–15% of activations in the book's running numbers. State the trade explicitly.

If items are being moved to Helpful but the user has no nudge plan, flag this — moved-and-buried is not progressive disclosure, it's hiding. Recommend the 4-element plan above.

Inputs

  • Current required-onboarding step list (or feature list to allocate)
  • The defined aha moment + smallest loop (output of aha-mapper if available)
  • Current activation funnel data, if any
  • (Optional) feature owners who would object — the book's gotcha is internal politics

Output structure

## Scope cut verdict: [HALVED | NEEDS_DEEPER_CUTS | NEEDS_MORE_EVIDENCE]

### Required (blocks the aha)
| Step | Why required | Minimum version |
|---|---|---|
| ... | ... | ... |

### Helpful (cut from onboarding, surfaced later)
| Step | Why cut | Re-surface trigger | Dismissible? |
|---|---|---|---|
| ... | ... | ... | ... |

### The cut
- Original required count: N
- Cut required count: M
- Reduction: ((N-M)/N)*100%

### Nudge sequence
[The 3-step post-aha surfacing plan for Helpful items]

### Expected activation impact
[1-2 sentences citing the book's 5-15%-per-step heuristic]

### Recommendation
[Concrete next step]

### Analogous case from the book
[A named example]

Worked example from the book

Calendly's original onboarding (Ch 4) → cut from 8 to 3 required

Original required steps (the team had argued each was essential):

  1. Sign up
  2. Connect a calendar
  3. Set default timezone
  4. Configure default duration
  5. Add a profile photo
  6. Set buffer time between meetings
  7. Create your first event type
  8. Copy your share link

Cut to required:

  1. Sign up
  2. Connect a calendar
  3. Copy your share link (a default event type is auto-created)

Moved to Helpful, surfaced after first booking:

  • Default timezone (auto-detected from browser; nudge only if booking came in from a different zone)
  • Default duration (nudged when user creates a second event type)
  • Profile photo (banner in user dashboard, dismissible)
  • Buffer time (advanced settings menu, not proactive)
  • Multiple event types (nudged after first 3 bookings completed)

Result: cut from 8 required steps to 3. Activation rate roughly doubled. The 5 moved items had no measurable activation impact when removed.

Gotchas

  • "Required" is a political negotiation, not a fact. Every team feels their thing must be onboarded. Forcing a 50% cut surfaces who has data and who has feelings.
  • Moving to Helpful without a re-surface plan = burying the feature. If you cut it and never bring it back, you've quietly killed it. Use the 4-element nudge plan or accept the kill.
  • The "minimum version" of a required step matters. "Connect a calendar" is required, but "connect ALL calendars in your org" is not. Reduce each required step to its smallest viable version.
  • Auto-detection beats prompting for any field that can be inferred. Timezone, locale, name — pull from browser/account, don't ask.

Anti-patterns to flag

If the user's plan has any of these, surface them:

  • Required-step list growing past 5 items — the book's running threshold; push back hard
  • Required fields that have a sensible default (timezone, duration) — default and let users change later, don't block
  • Moving items to "Optional in settings" without a proactive nudge plan — that's hiding, not disclosing
  • Required onboarding step that doesn't appear in the smallest loop — by definition it's not required; the team has scope creep

Source

Ch 3 (SLC scope cuts) and Ch 4 (Activation and the smallest loop).


About this skill

This skill is part of the ProductMind Skills catalog — open-source product-judgment skills for AI coding agents.

Source: Building Rocketships by Oji and Ezinne Udezue — Chapter 3. This skill applies one named framework from the book. It works standalone in any agent that supports the SKILL.md standard.

Want the orchestrated version? The RocketshipsGPT agent runs all 13 book skills together, with persistent memory, framework-fidelity evals, voice-checked output, and the book's anti-pattern catches built in. → rocketshipsgpt.productmind.co

License: Skill content licensed under CC BY-SA 4.0. Attribution required; derivative works must share alike. See ADR 0005 for rationale.

Skill version: 1.0.0 · Published: 2026-06-05

Frequently asked questions

What does the Scope Cutter AI skill do?

Use when the user is deciding what to cut from an onboarding flow, MVP scope, or feature list. Triggers on phrases like "cut scope", "what should we cut", "required vs optional", "progressive disclosure", "trim onboarding", "what's blocking activation", "the onboarding is too long". Implements the Required-vs-Helpful scope-cutting heuristics from Ch 3 and Ch 4 of Building Rocketships.

Why use Scope Cutter on TypingMind?

Because you install it once and use it with any model. Scope Cutter 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 Scope Cutter in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ojiudezue/productmind-skills/tree/main/skills/scope-cutter. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Scope Cutter?

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 Scope Cutter?

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

Is the Scope Cutter AI skill free?

It is published on GitHub by ojiudezue. Check the repository for licensing terms. 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 👇