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Iterate Lessons Log

Organization
product-on-purpose
iterate-lessons-log

Creates a structured lessons learned entry for organizational memory. Use after an incident, a completed project, or a significant learning to record knowledge for future teams and initiatives. Distinct from iterate-retrospective, which facilitates the team ceremony; this skill writes the durable lessons entry that outlives it.

Overview

Publisherproduct-on-purpose
Repositorypm-skills
Skill nameiterate-lessons-log
Stars
717
Forks
92
Bundled files
4
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.

  • 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 Lessons Log 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/product-on-purpose/pm-skills/tree/main/skills/iterate-lessons-log
  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/product-on-purpose/pm-skills.git /tmp/pm-skills
mkdir -p .claude/skills
cp -r /tmp/pm-skills/skills/iterate-lessons-log .claude/skills/iterate-lessons-log
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Iterate Lessons Log 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 Lessons Log 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 Lessons Log 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.

Lessons Log

A lessons log entry captures significant learning from projects, incidents, or experiences in a format that's useful to future teams who weren't there. Unlike retrospectives (which focus on team improvement), lessons logs focus on organizational knowledge that transcends individual teams.patterns, anti-patterns, and hard-won wisdom.

When to Use

  • After completing a significant project or initiative
  • Following a major incident, outage, or failure
  • When you realize something important that others should know
  • After discovering a pattern that keeps recurring
  • When experienced team members leave (capture their knowledge)
  • During post-mortems to preserve learnings

When NOT to Use

  • You are facilitating the team ceremony itself -> use iterate-retrospective; this skill banks the durable entry that outlives it
  • You are deciding whether to change direction based on results -> use iterate-pivot-decision
  • The learning is an experiment readout -> use measure-experiment-results first, then bank the transferable lesson here
  • You are updating stakeholders on what was learned -> use foundation-stakeholder-update

Instructions

When asked to create a lessons log entry, follow these steps:

  1. Choose a Descriptive Title Write a title that someone searching for this topic would find. Include keywords that describe the situation and the learning. Avoid generic titles like "Project X lessons."

  2. Provide Context Explain the situation fully enough that someone who wasn't there can understand it. Include the project, timeline, team, and any relevant constraints. Future readers need this context to assess applicability.

  3. Describe What Happened Write a factual account of what occurred. Be specific about actions taken, decisions made, and outcomes observed. Avoid blame.focus on events and systems.

  4. Extract the Lesson Articulate what you learned clearly. The lesson should be actionable.something others can apply. Distinguish between what you observed and your interpretation of why it matters.

  5. Formulate Recommendations Provide specific guidance for future teams facing similar situations. What should they do? What should they avoid? What questions should they ask?

  6. Define Applicability Help readers know when this lesson applies. What situations trigger relevance? What context makes it more or less applicable?

  7. Add Tags for Searchability Include keywords and categories that will help future searchers find this entry. Think about what someone would search for when facing a similar situation.

Output Format

Use the template in references/TEMPLATE.md to structure the output. A complete entry fills every template section: Metadata; Summary; Context; What Happened; The Lesson; Recommendations; Applicability; Supporting Evidence; Tags and Categories; and Review and Updates.

Quality Checklist

Before finalizing, verify:

  • Title is descriptive and searchable
  • Context is complete enough for someone who wasn't there
  • Lesson is clearly articulated and actionable
  • Recommendations are specific, not vague
  • Entry stands alone (doesn't require external context)
  • Tags enable future discovery

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 Lessons Log AI skill do?

Creates a structured lessons learned entry for organizational memory. Use after an incident, a completed project, or a significant learning to record knowledge for future teams and initiatives. Distinct from iterate-retrospective, which facilitates the team ceremony; this skill writes the durable lessons entry that outlives it.

Why use Iterate Lessons Log on TypingMind?

Because you install it once and use it with any model. Iterate Lessons Log 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 Lessons Log in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/product-on-purpose/pm-skills/tree/main/skills/iterate-lessons-log. 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 Lessons Log?

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 Lessons Log?

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

Is the Iterate Lessons Log 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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