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Pm Opportunity Scoring

Community
julianoczkowski
pm-opportunity-scoring

Score and rank product opportunities objectively with the Pragmatic Institute Opportunity Scoring model — across distinctive competency fit, competitive landscape, investment level, and impact to buyers/users. Use when the PM asks which idea to pursue, "score these opportunities", prioritize projects/bets, or compare options objectively instead of by opinion. Produces an Opportunity Scorecard as a Markdown or Word .docx artifact.

Overview

Publisherjulianoczkowski
Repositoryproduct-manager
Skill namepm-opportunity-scoring
Stars
51
Forks
7
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

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

Installation

Install the Pm Opportunity Scoring 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/julianoczkowski/product-manager/tree/main/skills/pm-opportunity-scoring
  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/julianoczkowski/product-manager.git /tmp/product-manager
mkdir -p .claude/skills
cp -r /tmp/product-manager/skills/pm-opportunity-scoring .claude/skills/pm-opportunity-scoring
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pm Opportunity Scoring 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 Pm Opportunity Scoring 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 Pm Opportunity Scoring 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.

Opportunity Scoring (Pragmatic Framework: Focus / Business)

Evaluate candidate opportunities objectively so a decision rests on evidence, not the loudest voice. Score each opportunity on four attributes using a 1-to-5 scale where 1 = Least Favorable and 5 = Most Favorable. See ../pm-copilot/references/framework.md.

The four attributes (1 = least favorable, 5 = most favorable)

AttributeWhat it measures1 (least) → 5 (most)
Distinctive CompetenciesHow much it relies on abilities we already have (valued, different, provable)1 = requires building a new competency → 5 = directly uses existing strong competencies
Competitive LandscapeSize/strength of alternatives1 = highly competitive (rival has pricing power/brand equity) → 5 = low competition (we can freeze out the market)
Investment LevelResources (people, material, facilities) required1 = very high (ground-up build) → 5 = very low (re-use existing assets)
Impact to Buyers/UsersConsequences for current & potential customers1 = negative outweighs positive → 5 = significant positive impact / high ROI for buyer

Total = sum of the four scores (4–20). Rank opportunities by total, but read the per-attribute scores too — a low Investment + high Impact "no brainer" may beat a higher total that depends on a competency you don't have.

Method

  1. List the candidate opportunities (ideally ones already validated as urgent, pervasive and willing-to-pay — see pm-market-problems).
  2. Score each attribute 1–5 and write the rationale (the evidence) for each score.
  3. Sum, rank, and discuss — especially where scores are low on Distinctive Competencies (can we really win?) or Investment (can we afford it?).

Interview the user for inputs (batch questions)

  1. What are the opportunities to compare? (Name each + the market problem it solves.)
  2. For each: do we already have the competencies to deliver it, or must we build them?
  3. How competitive is the space (who else, how entrenched)?
  4. Rough investment — reuse existing assets, or ground-up?
  5. Expected impact/ROI for buyers and users (and any downside)?

Artifact template

markdown
# Opportunity Scorecard — <product/BU>

**Company:** <company>  ·  **Feature / Product:** <feature / product name>
**Author:** <author>  ·  **Date created:** <date>  ·  **Version:** 1.0
**Scale:** 1 = Least Favorable → 5 = Most Favorable

| Opportunity | Distinctive Competencies | Competitive Landscape | Investment Level | Impact to Buyers/Users | Total | Rank |
| :--- | ---: | ---: | ---: | ---: | ---: | ---: |
| <Opportunity A> | 4 | 3 | 2 | 5 | 14 | 2 |
| <Opportunity B> | 5 | 4 | 4 | 4 | 17 | 1 |

## Rationale (evidence behind each score)
### <Opportunity A>
- **Distinctive Competencies (4):** <why>
- **Competitive Landscape (3):** <why>
- **Investment Level (2):** <why>
- **Impact to Buyers/Users (5):** <why>

## Recommendation
<Which opportunity(ies) to pursue and why — reference the scores and the market evidence.>

Deliver the artifact

Follow ../pm-copilot/references/artifact-output.md: confirm inputs, ask Markdown or .docx, write the .md, convert via your environment's native document-creation capability on request. Next stage: build the full business case for the winner with pm-product-canvas.

Frequently asked questions

What does the Pm Opportunity Scoring AI skill do?

Score and rank product opportunities objectively with the Pragmatic Institute Opportunity Scoring model — across distinctive competency fit, competitive landscape, investment level, and impact to buyers/users. Use when the PM asks which idea to pursue, "score these opportunities", prioritize projects/bets, or compare options objectively instead of by opinion. Produces an Opportunity Scorecard as a Markdown or Word .docx artifact.

Why use Pm Opportunity Scoring on TypingMind?

Because you install it once and use it with any model. Pm Opportunity Scoring 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 Pm Opportunity Scoring in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/julianoczkowski/product-manager/tree/main/skills/pm-opportunity-scoring. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Pm Opportunity Scoring?

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 Pm Opportunity Scoring?

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

Is the Pm Opportunity Scoring AI skill free?

Yes. It is published on GitHub by julianoczkowski 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.

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