sm:shape:risk-sequence

Identify load-bearing assumptions in product and design documents and rank them by cost-if-wrong.

5|2|Updated Mar 8, 2026

Search Tags:#prioritization #feasibility #assumptions #prd #experiment-design #desirability #risk-sequencing

Ready to run

npx skills add https://github.com/mnfst-ai/Stage_Manager_Skills --skill sm-shape-risk-sequence

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: sm:shape:risk-sequence
Source: https://github.com/mnfst-ai/Stage_Manager_Skills/tree/main/plugins/stage-manager/skills/shape-risk-sequence
Command: npx skills add https://github.com/mnfst-ai/Stage_Manager_Skills --skill sm-shape-risk-sequence

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps builders identify the load-bearing assumptions in a spec, design, or prompt and sequence work so the riskiest bets get proven (or retired) first, preventing wasted build effort and costly rework.

Core Features & Use Cases

Load-bearing assumption discovery: Reads PRDs, MRDs, architecture or design docs, prompts, or rough ideas and highlights statements that are treated as settled but untested.
Risk prioritization and sequencing: Ranks assumptions by cost-if-wrong (P1–P3), showing which experiments to run first to minimize downstream waste.
Actionable experiments: For each top risk, prescribes the smallest practical test to validate or invalidate the assumption and advises when to run it relative to other risks.
Use Case: Before writing prompts for Claude Code or starting a development sprint, run this Skill to get a 4–6 item risk-retirement map and concrete experiments.

Quick Start

Analyze the attached PRD and return 4-6 prioritized load-bearing assumptions with consequences if wrong and the smallest experiments to retire each P1.

Frequently Asked Questions about sm:shape:risk-sequence

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

FAQPage Schema

How do I identify load-bearing assumptions in a PRD before development?▼

To identify load-bearing assumptions in a PRD, you analyze the document to highlight untested statements treated as settled, then prioritize them by cost-if-wrong to sequence work and prevent wasted build effort.

How do I prioritize product risks by cost-if-wrong?▼

Prioritize product risks by ranking assumptions from P1 to P3 based on their cost-if-wrong, which sequences your experiments so the riskiest bets get proven or retired first to minimize downstream waste.

What is the best way to sequence experiments for untested assumptions?▼

The best way to sequence experiments for untested assumptions is to map them against their cost-if-wrong, then run the smallest practical tests for your P1 risks first to invalidate or validate them early.

Can I use risk sequencing on architecture docs and design specs?▼

Yes, you can use risk sequencing on architecture docs, design specs, MRDs, prompts, or rough ideas to extract load-bearing assumptions and determine what needs to be proven first before starting a development sprint.

How many assumptions should I prioritize in a risk-retirement map?▼

A risk-retirement map should produce a prioritized list of 4 to 6 assumptions, complete with consequences if wrong, P1 to P3 rankings, and the smallest experiments needed to retire top risks.