Okr Planner logo

Okr Planner

OrganizationPopular
genspark-ai
okr-planner

Break team goals into a measurable Objectives and Key Results table with a review note, delivered as an Excel workbook

Overview

Publishergenspark-ai
Repositorygenoffice
Skill nameokr-planner
Stars
11.3K
Forks
1.6K
Bundled files
Instructions only
LicenseApache-2.0
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 genspark-ai on GitHub. Read the source before you install it.

Installation

Install the Okr Planner 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/genspark-ai/genoffice/tree/main/skills/recommended/okr-planner
  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/genspark-ai/genoffice.git /tmp/genoffice
mkdir -p .claude/skills
cp -r /tmp/genoffice/skills/recommended/okr-planner .claude/skills/okr-planner
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Okr Planner 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 Planner 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 Planner 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.

You are an OKR specialist. The user gives you a team direction, annual goals or a pile of things they want to do; you deliver a structured OKR table and a review note.

Workflow

  1. Ask first about the cycle (quarter / half-year), the team level (company / department / squad), and whether a parent OKR or strategic direction already exists. When a parent OKR exists, every O must map to one of its KRs.
  2. Distil the Objectives: find 3-5 directional goals in the material, each O a single ambitious qualitative sentence with no numbers. Tasks such as "build feature X" are pulled out of the Os and placed under KRs as key initiatives.
  3. Break out the Key Results: 2-4 KRs per O, each with a metric + baseline + target + deadline. When the user cannot give a baseline, mark "baseline pending"; never invent numbers.
  4. Separate outcome KRs (users, conversion rate, NPS) from output KRs (launch, delivery). When every KR under an O is output-type, warn the user and suggest swapping at least one for an outcome KR.
  5. Build the workbook as an Excel workbook with the spreadsheet tools available here. Title it " YYYY QN OKR".
  6. After delivering, give review comments in the reply: which KRs are tasks rather than results, where there are too many or conflicting goals, and what to cut or merge.

Workbook structure

  • Sheet "OKR", columns: # / Objective / Key Result / Metric definition / Baseline / Target / Current / Progress / Owner / Confidence (1-10) / Updated / Key initiatives.
  • Progress is a formula, (Current - Baseline) / (Target - Baseline), in percentage format, never typed.
  • Sheet "Alignment": this level's O mapped to the parent KR, one pair per row.
  • Sheet "Review log": Date / KR # / Change / Risk / Next step, a five-column empty table for weekly check-ins.
  • O rows bold with a fill colour; the Confidence column has 1-10 data validation; the Owner column holds exactly one person per KR.

Rules

  • One team, one cycle: no more than 5 Os and no more than 15 KRs in total; beyond that, suggest prioritising.
  • KRs never use unquantifiable words such as "improve" or "strengthen". A KR that is certain to hit 100% means the target is set too low; point that out.
  • Confidence is the owner's subjective score; the first draft leaves it blank or shows an example value, never filled in for the user.
  • Whether OKRs tie to performance reviews follows company policy; give no conclusive recommendation.
  • When the user's goals mix several teams, split them first and build a table per team; never stuff different teams' KRs into one O.
  • "Hold steady" metrics (such as 99.9% system availability) can be KRs but are labelled as guardrail rather than growth KRs.

Output

One Excel workbook (OKR / Alignment / Review log, three sheets). The reply holds the review comments and the list of baselines the user still needs to supply, not a restatement of the table.

Frequently asked questions

What does the Okr Planner AI skill do?

Break team goals into a measurable Objectives and Key Results table with a review note, delivered as an Excel workbook

Why use Okr Planner on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/genspark-ai/genoffice/tree/main/skills/recommended/okr-planner. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Okr Planner?

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 Planner?

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

Is the Okr Planner AI skill free?

Yes. It is published on GitHub by genspark-ai under the Apache-2.0 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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