Agent skill

Meta Scenario Planning

by asgard-ai-platform in asgard-ai-platform/skills

Conduct scenario planning to prepare for multiple plausible futures using driving forces, uncertainty axes, and the 2x2 scenario matrix.

MITAuto-check passedTesting & QA

Install Meta Scenario Planning

skills CLI
$ npx skills add asgard-ai-platform/skills --skill meta-scenario-planning -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install asgard-ai-platform/skills meta-scenario-planning --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/meta-scenario-planning .claude/skills/meta-scenario-planning && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
meta-scenario-planning
GitHub stars
242
Token cost
~1k tokens
SKILL.md length
303 words
Files
3 (incl. references)
Skills in repo
207
Repo updated
First seen
Licence
MIT

At a glance

Conduct scenario planning to prepare for multiple plausible futures using driving forces, uncertainty axes, and the 2x2 scenario matrix.

  • Works in 5 steps: Identify driving forces: What… → Select two critical uncertainties: The… → Build the 2×2 matrix: Each axis is one… → …
  • The user faces high uncertainty
  • SKILL.md covers Framework, Output Format, Gotchas and References
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Meta Scenario Planning is an agent skill from asgard-ai-platform/skills. Conduct scenario planning to prepare for multiple plausible futures using driving forces, uncertainty axes, and the 2x2 scenario matrix. Use this skill when the user faces high uncertainty, needs to stress-test a strategy against different futures, or prepare contingency plans — even if they say 'what if things go wrong', 'what could the future look like', 'how do we prepare for uncertainty', or 'stress-test our strategy'.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `examples/sample_scenario.md` and `references/shell-method.md`).

It sits in Testing & QA, covering Accessibility and Load testing. The repository describes itself as: 301 open-source coding agent skills across 22 domains — methodology, judgment & gotchas packaged as Claude Agent Skills for the Asgard AI Platform. The licence is MIT.

When your agent uses it

  • The user faces high uncertainty
  • Needs to stress-test a strategy against different futures
  • Prepare contingency plans — even if they say what if things go wrong
  • What could the future look like

Example prompts

  • “what if things go wrong”
  • “what could the future look like”
  • “how do we prepare for uncertainty”
  • “/meta-scenario-planning”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Identify driving forces: What macro-forces will most shape the future? (technology, regulation, economy, demographics, competition)
  2. Select two critical uncertainties: The two most impactful forces with the most uncertain outcomes
  3. Build the 2×2 matrix: Each axis is one uncertainty with two endpoints (e.g., "regulation: strict vs lax")
  4. Name and describe four scenarios: Each quadrant is a distinct plausible future
  5. Test strategies against all four: Which strategies work in most/all scenarios? Which only work in one?

What it can do on your machine

Read from SKILL.md and the folder at commit 4e7f4f8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Meta Scenario Planning loads about 1k tokens when it runs, and up to ~6.1k if it reads all its reference files. Until then it costs about 112 tokens; SKILL.md has 303 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~112
When it runs · the whole SKILL.md, loaded when a task matches
~1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 303 words, ~1,008 tokens.

Download SKILL.mdSave it as .claude/skills/meta-scenario-planning/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
meta-scenario-planning
description
Conduct scenario planning to prepare for multiple plausible futures using driving forces, uncertainty axes, and the 2x2 scenario matrix. Use this skill when the user faces high uncertainty, needs to stress-test a strategy against different futures, or prepare contingency plans — even if they say 'what if things go wrong', 'what could the future look like', 'how do we prepare for uncertainty', or 'stress-test our strategy'.
metadata.category
WP-22 跨學科
metadata.tags
meta-thinking, scenario-planning, strategy, uncertainty

Scenario Planning

Framework

IRON LAW: Scenarios Are Not Predictions

Scenarios are PLAUSIBLE futures, not forecasts. The goal is NOT to predict
which future will happen, but to prepare strategies that work across
MULTIPLE possible futures. A strategy that only works in one scenario
is fragile.
The 2×2 Scenario Matrix Method
  1. Identify driving forces: What macro-forces will most shape the future? (technology, regulation, economy, demographics, competition)
  2. Select two critical uncertainties: The two most impactful forces with the most uncertain outcomes
  3. Build the 2×2 matrix: Each axis is one uncertainty with two endpoints (e.g., "regulation: strict vs lax")
  4. Name and describe four scenarios: Each quadrant is a distinct plausible future
  5. Test strategies against all four: Which strategies work in most/all scenarios? Which only work in one?
Process

Step 1: Driving Forces (brainstorm 10-15)

  • Political, economic, social, technological, environmental, competitive
  • Rate each on: Impact (H/M/L) × Uncertainty (H/M/L)
  • High Impact + High Uncertainty → candidate for axes

Step 2: Select Two Axes

  • Choose two forces that are both high-impact AND high-uncertainty
  • They should be independent of each other (not correlated)

Step 3: Build Four Scenarios

  • Give each scenario a memorable name (not "Scenario 1")
  • Write a 1-paragraph narrative for each: what does this world look like in 5-10 years?

Step 4: Strategy Testing

  • For each strategy option, assess: does it work in this scenario? (Yes / Partial / No)
  • Robust strategies work in 3-4 scenarios. Fragile strategies work in only 1.

Output Format

markdown
# Scenario Planning: {Context}

## Driving Forces
| Force | Impact | Uncertainty | Selected? |
|-------|--------|------------|-----------|
| {force} | H/M/L | H/M/L | ✓/— |

## Scenario Matrix
- Axis 1: {Uncertainty A} — {endpoint 1} vs {endpoint 2}
- Axis 2: {Uncertainty B} — {endpoint 1} vs {endpoint 2}

| | {A: endpoint 1} | {A: endpoint 2} |
|---|---|---|
| **{B: endpoint 1}** | **"{Scenario Name}"**: {narrative} | **"{Scenario Name}"**: {narrative} |
| **{B: endpoint 2}** | **"{Scenario Name}"**: {narrative} | **"{Scenario Name}"**: {narrative} |

## Strategy Robustness Test
| Strategy | Scenario 1 | Scenario 2 | Scenario 3 | Scenario 4 |
|----------|-----------|-----------|-----------|-----------|
| {strategy A} | ✓/△/✗ | ✓/△/✗ | ✓/△/✗ | ✓/△/✗ |

## Robust Strategies
{Strategies that work in most scenarios}

## Contingency Triggers
- If {early signal}, activate {contingency plan for scenario X}

Gotchas

  • Scenarios should be uncomfortable: If all four scenarios are comfortable, you haven't explored enough uncertainty. Include at least one scenario you'd rather not think about.
  • Avoid "good/bad" framing: Scenarios aren't optimistic vs pessimistic. Each scenario has opportunities AND threats. A "strict regulation" world is bad for some and good for others.
  • Early warning signals: Identify observable indicators that signal which scenario is unfolding. This converts scenarios into actionable intelligence.
  • Two axes is a simplification: Reality has many uncertainties. The 2×2 is a tool for clarity, not completeness. Consider additional driving forces as variations within scenarios.

References

  • For Shell's original scenario planning methodology, see references/shell-method.md

© asgard-ai-platform, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in meta-scenario-planning of asgard-ai-platform/skills.

  • SKILL.md
  • examples/sample_scenario.md
  • references/shell-method.md

Open the folder on GitHubat commit 4e7f4f8

Compare with similar skills

Meta Scenario Planning next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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iOS Accessibility Testingconorluddy/xclaude-plugin183—~5kAutomated safety check: PassMIT
Accessibility Testing StrategyOwl-Listener/inclusive-design-skills105—~1kAutomated safety check: PassMIT
Scoutqa Testgithub/awesome-copilot40k1 repos~3.5kAutomated safety check: PassMIT
Performance Engineeringancoleman/ai-design-components525—~2.9kAutomated safety check: NotesMIT

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Questions about Meta Scenario Planning

What does Meta Scenario Planning do?

Conduct scenario planning to prepare for multiple plausible futures using driving forces, uncertainty axes, and the 2x2 scenario matrix. Meta Scenario Planning is an agent skill from asgard-ai-platform/skills. Conduct scenario planning to prepare for multiple plausible futures using driving forces, uncertainty axes, and the 2x2 scenario matrix.

When should I use Meta Scenario Planning?

Meta Scenario Planning fits situations like: the user faces high uncertainty; needs to stress-test a strategy against different futures; prepare contingency plans — even if they say what if things go wrong; what could the future look like.

How do I install Meta Scenario Planning in Claude Code?

Run `npx skills add asgard-ai-platform/skills --skill meta-scenario-planning -a claude-code`. Or copy the skill folder (meta-scenario-planning in asgard-ai-platform/skills) into .claude/skills/meta-scenario-planning in your project. Claude Code loads it when a task matches its description.

How do I install Meta Scenario Planning in Codex?

Run `npx skills add asgard-ai-platform/skills --skill meta-scenario-planning -a codex`. Or copy the skill folder (meta-scenario-planning in asgard-ai-platform/skills) into .agents/skills/meta-scenario-planning in your project. Codex loads it when a task matches its description.

Can I use Meta Scenario Planning in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add asgard-ai-platform/skills --skill meta-scenario-planning -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/meta-scenario-planning, .gemini/skills/meta-scenario-planning, .github/skills/meta-scenario-planning and .opencode/skills/meta-scenario-planning in your project.

What does Meta Scenario Planning need to run?

SKILL.md names no scripts, command-line tools or credentials: Meta Scenario Planning is instructions for the agent only.

Does Meta Scenario Planning access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Meta Scenario Planning safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Meta Scenario Planning use?

Meta Scenario Planning is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Meta Scenario Planning use?

About 1k tokens (SKILL.md is roughly 4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.1k tokens, read only when the agent opens those files.

What are the alternatives to Meta Scenario Planning?

Skills that share tags, products or a category with Meta Scenario Planning: Web Testing with Playwright and Vitest (withkynam/vibecode-pro-max-kit, 1.1k stars), iOS Accessibility Testing (conorluddy/xclaude-plugin, 183 stars), Accessibility Testing Strategy (Owl-Listener/inclusive-design-skills, 105 stars) and Scoutqa Test (github/awesome-copilot, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Meta Scenario Planning?

asgard-ai-platform (a GitHub organization) maintains it in asgard-ai-platform/skills, which has 242 GitHub stars. The repository holds 207 skills in this directory. The repository was last updated on June 6, 2026.

Source: asgard-ai-platform/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.