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Stakeholder Update

Community
Mehdibargach
stakeholder-update

Turn raw notes into a polished stakeholder update. Supports email, Slack message, or deck bullet points. Takes messy notes and outputs a clear, structured update with TL;DR, progress, blockers, and asks.

Overview

PublisherMehdibargach
Repositoryclaude-code-pm-skills
Skill namestakeholder-update
Stars
97
Forks
38
Bundled files
Instructions only
Links
Skill sourceRepository
  • 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 Mehdibargach on GitHub. Read the source before you install it.

Installation

Install the Stakeholder Update 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/Mehdibargach/claude-code-pm-skills/tree/main/skills/stakeholder-update
  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/Mehdibargach/claude-code-pm-skills.git /tmp/claude-code-pm-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-pm-skills/skills/stakeholder-update .claude/skills/stakeholder-update
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Stakeholder Update 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 Stakeholder Update 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 Stakeholder Update 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.

Stakeholder Update

Transform scattered notes into a crisp stakeholder update. Executives skim — make every sentence earn its place.

Process

  1. Ingest raw notes. Read the input — meeting notes, bullet points, pasted Slack threads, status updates, whatever the user provides.
  2. Identify the format. Default is email. User can request: email, Slack message, or deck bullets. Adjust tone and structure accordingly.
  3. Extract key information. Categorize everything into: progress (shipped/moved), blockers (stuck/needs help), decisions needed (specific asks), and upcoming priorities.
  4. Write the TL;DR. Two sentences max. The most important thing and the one thing you need from the reader.
  5. Structure the update. Follow the output format for the chosen medium.
  6. Quantify. Replace vague statements with specifics. "Good progress" becomes "shipped 3 of 5 planned features."

Output Format

Email Format (default)

Subject: [Project/Team] Update — [Date or Sprint]

**TL;DR:** [Two sentences. What happened + what you need.]

**Progress**
- [What shipped or moved forward — be specific]
- [What shipped or moved forward]
- [What shipped or moved forward]

**Blockers**
- [What is stuck] — Need [specific help] from [specific person/team]
- [What is stuck] — Need [specific help]

**Decisions Needed**
- [Specific question requiring a yes/no or choice] — Deadline: [date]
- [Specific question] — Deadline: [date]

**Next Week**
- [Priority 1]
- [Priority 2]
- [Priority 3]

Slack Format

*[Project] Update — [Date]*

*TL;DR:* [Two sentences]

*Shipped:* [bullet list]
*Blocked:* [bullet list with specific asks]
*Need from you:* [decisions or actions with deadlines]

Deck Bullets Format

[Title slide content]
- Key metric: [number]
- Shipped: [list]
- On track / At risk / Blocked: [status]
- Decision needed: [one line]

Rules

  • The TL;DR is the most important part. Many readers will stop there. Make it count.
  • No jargon. If a technical term is necessary, add a parenthetical explanation.
  • Be specific. "Making progress on the API" is useless. "API endpoints 4/6 complete, remaining 2 blocked on auth service migration" is useful.
  • Quantify everything possible. Numbers, percentages, dates, counts.
  • Blockers must include what you need and from whom. A blocker without an ask is just a complaint.
  • Decisions needed must be framed as specific questions with options if possible, not open-ended problems.
  • Keep it short. Email: under 200 words. Slack: under 100 words. Deck: under 50 words.
  • Do not editorialize or add opinions not present in the raw notes. Synthesize, do not embellish.
  • If the raw notes are too thin to write a meaningful update, say so and ask for more context rather than padding.

Frequently asked questions

What does the Stakeholder Update AI skill do?

Turn raw notes into a polished stakeholder update. Supports email, Slack message, or deck bullet points. Takes messy notes and outputs a clear, structured update with TL;DR, progress, blockers, and asks.

Why use Stakeholder Update on TypingMind?

Because you install it once and use it with any model. Stakeholder Update 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 Stakeholder Update in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Mehdibargach/claude-code-pm-skills/tree/main/skills/stakeholder-update. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Stakeholder Update?

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 Stakeholder Update?

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

Is the Stakeholder Update AI skill free?

It is published on GitHub by Mehdibargach. 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.

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