Iterate Refinement Notes

Organization

product-on-purpose

iterate-refinement-notes

Documents backlog refinement session outcomes including stories refined, estimates, questions raised, and decisions made. Use during or after refinement to capture the results and share with absent team members.

Overview

Publisher	product-on-purpose
Repository	`pm-skills`
Skill name	`iterate-refinement-notes`
Stars	717
Forks	92
Bundled files	4
License	Apache-2.0
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.
4 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by product-on-purpose on GitHub. Read the source before you install it.

Installation

Install the Iterate Refinement Notes 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/product-on-purpose/pm-skills/tree/main/skills/iterate-refinement-notes
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/product-on-purpose/pm-skills/tree/main/skills/iterate-refinement-notes

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/product-on-purpose/pm-skills.git /tmp/pm-skills
mkdir -p .claude/skills
cp -r /tmp/pm-skills/skills/iterate-refinement-notes .claude/skills/iterate-refinement-notes

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

Use it in TypingMind

Enable Iterate Refinement Notes 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 Iterate Refinement Notes 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 Iterate Refinement Notes 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.

Refinement Notes

Refinement notes capture the outcomes of backlog refinement (grooming) sessions.what was discussed, what was estimated, and what decisions were made. They serve as a quick reference for team members who missed the session and a historical record of how stories evolved from idea to ready-for-sprint.

When to Use

During refinement sessions to capture decisions in real-time
After refinement to share outcomes with absent team members
When onboarding new team members to explain backlog context
Before sprint planning to review what's been refined
When stories need re-refinement due to time elapsed

When NOT to Use

You need the stories themselves written -> use deliver-user-stories
You need a general meeting summary, not a backlog-refinement record -> use foundation-meeting-recap
You are running the retrospective ceremony -> use iterate-retrospective
Refined stories need their failure scenarios enumerated -> use deliver-edge-cases

Instructions

When asked to document refinement notes, follow these steps:

Record Session Metadata Note the date, attendees, and duration. This helps track who was part of decisions and when discussions happened.
List Stories Discussed For each story, capture the outcome: estimated points, refined status, key discussion points, and any modifications made to the original scope.
Document Questions Raised Questions that couldn't be answered in the session need owners and due dates. Don't let them disappear.they often block sprint planning.
Capture Decisions Made Record any scope decisions, technical approaches agreed upon, or priority changes. These decisions are valuable context that gets lost without documentation.
Note Action Items Any follow-up work needed before stories are sprint-ready: mockups to create, technical spikes to run, stakeholders to consult.
Flag Blocked Stories Clearly identify stories that can't proceed until blockers are resolved. Include what the blocker is and who owns resolution.
Plan Next Session Note what should be refined next and any preparation needed.

Output Format

Use the template in references/TEMPLATE.md to structure the output. Complete notes fill every template section: Session Info; Summary; Stories Refined; Stories Summary Table; Questions Raised; Decisions Made; Action Items; Blocked Stories; Parking Lot; and Next Session.

Quality Checklist

Before finalizing, verify:

All discussed stories have outcomes recorded
Open questions have owners assigned
Decisions are captured with enough context
Blocked stories are clearly flagged
A reader who missed the session can tell each story's outcome and what happens next without asking

Examples

See references/EXAMPLE.md for a completed example.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Iterate Refinement Notes AI skill do?

Why use Iterate Refinement Notes on TypingMind?

Because you install it once and use it with any model. Iterate Refinement Notes 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 Iterate Refinement Notes in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/product-on-purpose/pm-skills/tree/main/skills/iterate-refinement-notes. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Iterate Refinement Notes?

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 Iterate Refinement Notes?

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

Is the Iterate Refinement Notes AI skill free?

Yes. It is published on GitHub by product-on-purpose 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Refinement Notes

When to Use

When NOT to Use

Instructions

Output Format

Quality Checklist

Examples

Bundled files

Frequently asked questions

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