S4h Decision Option Mapping logo

S4h Decision Option Mapping

Organization
human-avatar
s4h-decision-option-mapping

Ensures all real options are visible before choosing — countering the false dichotomy that limits consideration to the first two options that came to mind. Triggers: 'what are all the options', 'false dichotomy check', 'expand the option set', 'what else could we do', 'options inventory'.

Overview

Publisherhuman-avatar
Repositoryskills-for-humanity
Skill names4h-decision-option-mapping
Stars
234
Forks
24
Bundled files
Instructions only
LicenseMIT
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 human-avatar on GitHub. Read the source before you install it.

Installation

Install the S4h Decision Option Mapping 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/human-avatar/skills-for-humanity/tree/main/skills/s4h-decision-option-mapping
  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/human-avatar/skills-for-humanity.git /tmp/skills-for-humanity
mkdir -p .claude/skills
cp -r /tmp/skills-for-humanity/skills/s4h-decision-option-mapping .claude/skills/s4h-decision-option-mapping
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable S4h Decision Option Mapping 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 S4h Decision Option Mapping 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 S4h Decision Option Mapping 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 Option Mapping

The options people choose between are usually not all the options that exist — they are the first options that were named, which then anchored the frame. This skill expands the option set before analysis begins, using four specific moves that reliably surface options the natural framing excludes.


Your Process

Step 1: State the Decision and Currently-Considered Options Write the decision as currently framed and list all options currently on the table. Don't filter yet — include the options even if they seem weak.

Framing check: Confirm the specific decision and its intended outcome before continuing. State what you've identified — the actual decision being mapped and the goal it serves — in one sentence, then use AskUserQuestion:

  • Question: "I'm reading this as: [your one-sentence framing of the decision and its intended outcome]. Is that right?"
  • Header: "Framing"
  • Options:
    • Yes — proceed — framing is correct
    • Adjust — one element is off; user will correct it before you continue
    • Reframe — different situation than read; incorporate the correction before proceeding

Step 2: Challenge the Frame Is this decision actually forced? Are you choosing between options A and B because those are the real options, or because those are the options that were generated first? What would have to be true for there to be no decision to make?

Step 3: Four Expansion Moves

(a) Expand: Generate 3 more ways to achieve the underlying goal. Not variations on existing options — genuinely different approaches. Ask: if none of the current options existed, what would we try?

(b) Defer: Is "decide later" viable? At what cost? Deferral is a real option — it has costs and benefits like any other. When can this be decided without foreclosing anything important?

(c) Hybrid: Can elements of multiple options be combined? Hybrids often emerge when options are treated as mutually exclusive when they aren't.

(d) Reframe: If the goal were slightly different, what options appear? Sometimes the option set is limited by the goal framing, not the constraints.

Step 4: Add Viable New Options Before narrowing: Show the complete generated set to the user first. Use AskUserQuestion:

  • Question: "I've identified [N] options across the four expansion moves. Before I select the genuinely viable ones, are there any you'd flag as especially important, or any I've missed?"
  • Header: "Prioritise"
  • Options:
    • Proceed with your selection — the set looks right
    • Flag one — user will name a specific option to include
    • Add a missing one — user will describe it

From the four moves, add the options that are genuinely viable. Discard the ones that don't survive basic scrutiny — not to narrow prematurely, but to keep the set useful.

Step 5: Recommend Next Step With the expanded set, recommend which analytical tool to apply: decision-criteria- weighting (multiple comparable options), decision-reversibility-analysis (one option being considered), or decision-premortem-analysis (a direction already being leaned toward).


Human Check-in

Before proceeding, use the AskUserQuestion tool. State your interpretation of the situation in 1–2 sentences — what is being analyzed and what the core question is — then ask:

  • Question: "My read: [your 1–2 sentence interpretation]. How do you want to proceed?"
  • Header: "Scope"
  • Options:
    • Full analysis — Complete all steps, reasoning shown throughout
    • Key findings only — Bottom-line output, skip step-by-step detail
    • Hidden options only — Surface the options not currently being considered
    • Reframe — The read is off; correct it and the analysis will follow the corrected framing

Proceed based on their selection. If the user reframes, incorporate the correction before running any analysis.

Output Format

Decision as framed: [Statement] Currently-considered options: [List]

Frame challenge:

[Is this decision forced? What assumptions are built into the current option set?]

Expanded option set:

OptionSource (original / expand / defer / hybrid / reframe)Viable?Reason

Options to add to the decision:

[Bulleted list with one-line rationale each]

Recommended next step:

[Which analytical skill to apply, and to which expanded option set]


Notes

The most commonly missed option is deferral. "Decide now" is itself a choice with costs — urgency is often assumed rather than real, and deferral with a defined review point is frequently the most rational option on the table.


What's Next

After delivering this output, use AskUserQuestion to offer the next move:

  • Question: "Options mapped. What's next?"
  • Header: "Next"
  • Options:
    • /s4h-decision-criteria-weighting — Evaluate the options you've mapped against weighted criteria
    • /s4h-decision-premortem-analysis — Stress-test the leading option before committing
    • /s4h-probability-scenario-weighting — Weight options by their probability of success
    • Done — Wrap up and synthesise what we have so far

Frequently asked questions

What does the S4h Decision Option Mapping AI skill do?

Ensures all real options are visible before choosing — countering the false dichotomy that limits consideration to the first two options that came to mind. Triggers: 'what are all the options', 'false dichotomy check', 'expand the option set', 'what else could we do', 'options inventory'.

Why use S4h Decision Option Mapping on TypingMind?

Because you install it once and use it with any model. S4h Decision Option Mapping 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 S4h Decision Option Mapping in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/human-avatar/skills-for-humanity/tree/main/skills/s4h-decision-option-mapping. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use S4h Decision Option Mapping?

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 S4h Decision Option Mapping?

As many as you like. As long as a model supports skills, you can use S4h Decision Option Mapping with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the S4h Decision Option Mapping AI skill free?

Yes. It is published on GitHub by human-avatar under the MIT 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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