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Decision Doc

Community
Mehdibargach
decision-doc

Structure a product decision with options, trade-offs, and a clear recommendation. Takes a decision to make and outputs a concise decision document ready for stakeholder review.

Overview

PublisherMehdibargach
Repositoryclaude-code-pm-skills
Skill namedecision-doc
Stars
97
Forks
38
Bundled files
Instructions only
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 Mehdibargach on GitHub. Read the source before you install it.

Installation

Install the Decision Doc 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/decision-doc
  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/decision-doc .claude/skills/decision-doc
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Decision Doc 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 Decision Doc 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 Decision Doc 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.

Decision Doc

Turn ambiguity into a structured decision. One page, clear options, explicit trade-offs, and a recommendation you can defend.

Process

  1. Frame the decision. What exactly are we deciding? Why now? What happens if we do nothing?
  2. Identify constraints. Time, budget, technical limitations, dependencies, organizational politics.
  3. Generate options. 2-4 realistic options. Always include "do nothing" if it is viable. Each option must be genuinely different, not variations of the same idea.
  4. Evaluate each option. Pros, cons, effort estimate, risk level, and reversibility.
  5. Make a recommendation. Pick one. State why. Be explicit about what you are giving up.
  6. Define next steps. If approved, what happens on Day 1?

Output Format

## Decision: [One-line framing of the decision]

### Context
[2-3 sentences. Why this decision matters now. What triggered it. What happens if we delay.]

### Constraints
- [Constraint 1]
- [Constraint 2]
- [Constraint 3]

### Options

#### Option A: [Name]
[1-2 sentence description]
- **Pros:** [list]
- **Cons:** [list]
- **Effort:** [T-shirt size + calendar time]
- **Risk:** [Low/Medium/High — one sentence why]

#### Option B: [Name]
[1-2 sentence description]
- **Pros:** [list]
- **Cons:** [list]
- **Effort:** [T-shirt size + calendar time]
- **Risk:** [Low/Medium/High — one sentence why]

#### Option C: [Name] (if applicable)
[same structure]

### Comparison
| Criteria | Option A | Option B | Option C |
|----------|----------|----------|----------|
| Speed to value | [fast/medium/slow] | ... | ... |
| User impact | [high/medium/low] | ... | ... |
| Effort | [S/M/L/XL] | ... | ... |
| Risk | [low/med/high] | ... | ... |
| Reversibility | [easy/hard] | ... | ... |

### Recommendation
**Go with Option [X].**
[2-3 sentences. Why this option wins. What specific factor tips the balance.]

### What We're Giving Up
[Be explicit. Every choice has a cost. Name it.]

### Reversibility
[Can we change course later? At what cost? By when does this become irreversible?]

### Next Steps (if approved)
1. [Action] — [Owner] — [By when]
2. [Action] — [Owner] — [By when]
3. [Action] — [Owner] — [By when]

Rules

  • Always make a recommendation. A decision doc without a recommendation is just a menu. Take a position.
  • "Do nothing" is a valid option. Include it when inaction is genuinely viable, and be honest about its costs.
  • Pros and cons must be specific to the decision, not generic. "Faster time to market" is only a pro if you explain faster than what and why speed matters here.
  • Never present more than 4 options. If there are more, you have not narrowed the problem enough.
  • Reversibility is mandatory. Irreversible decisions deserve more analysis. Reversible ones deserve faster action.
  • The "What We're Giving Up" section is non-negotiable. Decisions without acknowledged trade-offs are not real decisions.
  • Keep it to one page. If the decision doc is longer than 2 pages, the decision is probably two decisions. Split it.
  • If the input is too vague to generate meaningful options, ask clarifying questions. Do not fabricate context.

Frequently asked questions

What does the Decision Doc AI skill do?

Structure a product decision with options, trade-offs, and a clear recommendation. Takes a decision to make and outputs a concise decision document ready for stakeholder review.

Why use Decision Doc on TypingMind?

Because you install it once and use it with any model. Decision Doc 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 Decision Doc in TypingMind?

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

Which AI models can use Decision Doc?

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 Decision Doc?

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

Is the Decision Doc 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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