Okr Structuring

Q: Why use Okr Structuring on TypingMind?

Because you install it once and use it with any model. Okr Structuring 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.

Q: How do I install Okr Structuring in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/okr-structuring. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Q: Which AI models can use Okr Structuring?

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.

Q: How many AI models can I use with Okr Structuring?

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

Q: Is the Okr Structuring AI skill free?

It is published on GitHub by Productfculty-aipm. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

Q: 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.

Q: 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.

Community

Productfculty-aipm

okr-structuring

Use this skill when the user asks to "write OKRs", "structure our OKRs", "help with quarterly goals", "OKR review", "are our OKRs good", "how do I write key results", "our objectives and key results", "check our OKRs", or wants to create, review, or improve their OKR structure. Also use this skill when the user's roadmap items don't clearly connect to stated objectives.

Overview

Publisher	Productfculty-aipm
Repository	`PM-Copilot-by-Product-Faculty`
Skill name	`okr-structuring`
Stars	80
Forks	34
Bundled files	Instructions only
Links	Skill source Repository Homepage

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 Productfculty-aipm on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/okr-structuring
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/okr-structuring

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/Productfculty-aipm/PM-Copilot-by-Product-Faculty.git /tmp/PM-Copilot-by-Product-Faculty
mkdir -p .claude/skills
cp -r /tmp/PM-Copilot-by-Product-Faculty/skills/okr-structuring .claude/skills/okr-structuring

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Okr Structuring 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 Okr Structuring 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 Okr Structuring 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.

OKR Structuring

You are helping the user write or review OKRs that encode genuine strategic intent — not just activity tracking. The goal is OKRs that make roadmap prioritization decisions obvious and tell the product story to leadership.

Frameworks: Marty Cagan (outcomes not output), Shreyas Doshi (strategy vs. execution levels), John Doerr (Measure What Matters).

Step 1 — Load Context

Read memory/user-profile.md for current bets, North Star, and roadmap state. Read context/product/roadmap.md for current objectives. Read context/company/mission.md for company-level direction.

Step 2 — OKR Quality Criteria

Before writing or reviewing, establish the quality bar:

Objective quality:

Is it inspirational and outcome-oriented, not a list of tasks?
Does it connect clearly to the company mission or North Star?
Would a smart person outside the team understand why this matters?
Is it achievable within the timeframe with a real stretch required?

Key Result quality:

Is it a metric with a baseline, target, and timeframe — not a milestone?
Does it measure an outcome the user cares about, not a delivery ("ship feature X")?
Is it independently measurable — not dependent on another KR?
Is it achievable with 70–80% confidence? (Too easy = no stretch; too hard = gives up)

Step 3 — The Output vs. Outcome Test

For each objective and key result, apply the test:

❌ Output-framed (bad): "Ship the new onboarding flow" — this measures delivery, not impact ✓ Outcome-framed (good): "Increase 7-day activation rate from 61% to 75%" — this measures what matters

Common outputs disguised as outcomes:

"Launch X" → Ask: what changes for users when X launches?
"Increase X feature adoption to Y%" → Ask: does feature adoption translate to the outcome that matters?
"Complete X research project" → Ask: what decision does this enable?

Help the user reframe all output-framed KRs.

Step 4 — OKR Architecture

Structure OKRs in a clear hierarchy:

Company-level OKR: What the whole company is trying to achieve

Team-level OKR: What the product team contributes toward the company OKR
- Project-level KRs: What specific initiatives move the team KR

Make sure each level clearly ladders up. A team OKR that doesn't connect to a company OKR is either a supporting objective (maintenance, tech debt) or misaligned.

Step 5 — Number of OKRs

Recommend the right number based on team size and stage:

Solo PM / founding PM (from memory): 1–2 objectives, 2–3 KRs each — focus is your competitive advantage
Small team (< 10): 2–3 objectives, 2–4 KRs each
Larger team: 3–4 objectives, no more than 5 KRs each

More OKRs = everything is a priority = nothing is.

Step 6 — Write or Review

If writing from scratch: Produce a full OKR set with:

1–3 objectives
2–4 KRs per objective
Brief rationale for why each KR is the right measure

If reviewing existing OKRs: Score each OKR on the quality criteria (Step 2) and provide:

What's working
What to change
Rewritten versions of any weak objectives or key results

Step 7 — Roadmap-OKR Linkage Check

After OKRs are established, check alignment with the roadmap from memory or context/product/roadmap.md:

For each Now item: which KR does it serve?
For each KR: is there at least one Now or Next item that moves it?
Any KR with no roadmap item pointing at it is either a gap (we need something) or a wrong KR (it doesn't translate to buildable work)
Any roadmap item that doesn't serve a KR is either maintenance (fine, label it so) or misaligned (discuss with team)

Output a simple alignment table.

Frequently asked questions

What does the Okr Structuring AI skill do?

Why use Okr Structuring on TypingMind?

Because you install it once and use it with any model. Okr Structuring 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 Okr Structuring in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/okr-structuring. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Okr Structuring?

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 Okr Structuring?

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

Is the Okr Structuring AI skill free?

It is published on GitHub by Productfculty-aipm. 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

Brand Voice

affaan-m

CommunityPopular

Build a source-derived writing style profile from real posts, essays, launch notes, docs, or site copy, then reuse that profile across content, outreach, and social workflows. Use when the user wants…

Competitive Platform Analysis

affaan-m

CommunityPopular

Use when scoping a competitive landscape — identifying, categorising, and score-filtering a competitor set before any benchmarking begins. Decides who counts as a competitor, which tier they belong…

Content Engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content…

Domain Modeling

Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a CONTEXT.md, or recording or editing an ADR.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

OKR Structuring

Step 1 — Load Context

Step 2 — OKR Quality Criteria

Step 3 — The Output vs. Outcome Test

Step 4 — OKR Architecture

Step 5 — Number of OKRs

Step 6 — Write or Review

Step 7 — Roadmap-OKR Linkage Check

Frequently asked questions

Related AI Skills

Set up your own AI workspace now