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harrylabsj

Decision Forest

by haidong · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install decision-forest
Description
Map a decision into options, non-negotiables, criteria, best/base/worst cases, reversibility, and a review checkpoint. Use when the user is comparing multipl...
README (SKILL.md)

Decision Forest

Overview

Use this skill to slow a messy decision down enough to see what actually matters. It helps the user define the real question, compare options branch by branch, separate facts from assumptions and fears, and end with either a provisional choice or a clearly bounded next test.

This skill is descriptive only. It does not provide legal, medical, or financial advice, and it does not predict outcomes.

Trigger

Use this skill when the user wants to:

  • compare two or more life, work, or project options
  • stop mixing facts, fears, and imagined outcomes together
  • add reversibility and future-regret checks to a decision
  • narrow a crowded option set
  • choose a small test instead of forcing immediate certainty

Example prompts

  • "Help me decide whether to stay in my job or start a small consulting business"
  • "Build a decision tree for moving, waiting, or testing a smaller version"
  • "I am stuck between two options and I cannot see what matters most"
  • "Map best case, base case, and worst case for this decision"

Workflow

  1. Define the decision in one sentence.
  2. List the visible options and the hidden option of delaying or testing a smaller version.
  3. Identify non-negotiables and decision criteria.
  4. Build branches for each option.
  5. Sketch best case, base case, and worst case outcomes.
  6. Check reversibility and future regret.
  7. Recommend a provisional choice and a review checkpoint.

Inputs

The user can provide any mix of:

  • the decision question
  • visible options
  • deadline or time pressure
  • constraints and non-negotiables
  • known facts or data points
  • fears, hopes, or gut reactions
  • practical criteria, such as cost, time, energy, meaning, family impact, or reversibility

Outputs

Return a markdown decision brief with:

  • decision trunk summary
  • non-negotiables and criteria
  • branch review for each option
  • best, base, and worst cases
  • reversibility and key unknowns
  • provisional choice logic and review date

Safety

  • Keep facts, assumptions, and fears visibly separate.
  • High-stakes legal, medical, or financial decisions may need expert advice beyond heuristics.
  • Do not claim certainty the information cannot support.
  • When uncertainty is high, prefer a smaller reversible test over forced confidence.

Acceptance Criteria

  • Return markdown text.
  • Include at least three meaningful criteria.
  • Show reversibility for each branch.
  • End with either a provisional choice or a very clear next test.
Usage Guidance
This skill appears to do exactly what it says: parse your decision text and produce a structured markdown decision brief. It only reads its own SKILL.md and the user input; it does not access environment variables, remote endpoints, or install additional software. Be aware the decision logic uses simple text heuristics (keyword matching), so outputs may be blunt or miss nuance; treat its recommendations as a structured prompt for your own judgment rather than expert legal/medical/financial advice.
Capability Analysis
Type: OpenClaw Skill Name: decision-forest Version: 1.0.0 The 'decision-forest' skill is a text-processing utility designed to help users structure complex decisions. The Python logic in handler.py uses basic regex and keyword matching to categorize user input into facts, fears, and options, and the SKILL.md instructions are strictly aligned with this decision-aid purpose without any high-risk behaviors or prompt-injection risks.
Capability Assessment
Purpose & Capability
Name/description match the implementation: the handler parses user text into a decision brief, extracts options/criteria/fears/etc., and renders markdown. No unrelated credentials, binaries, or external services are requested.
Instruction Scope
SKILL.md instructs the agent to build a decision tree and return markdown. The code follows those instructions. The only non-user data access is reading the local SKILL.md file for metadata, which is consistent with the skill packaging.
Install Mechanism
There is no install specification (instruction-only from a platform perspective). The package includes source files but does not declare downloads or external installers. No archives or remote URLs are fetched in the code.
Credentials
The skill requires no environment variables, credentials, or config paths. The code does not access os.environ beyond locating its own SKILL.md and has no network calls or secret-handling behavior.
Persistence & Privilege
The skill is not always-enabled and does not modify other skills or system-wide settings. It does not write files or persist credentials; its file I/O is limited to reading its own SKILL.md.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install decision-forest
  3. After installation, invoke the skill by name or use /decision-forest
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of the Decision Forest skill. - Guides users through structured decision-making with options, criteria, and non-negotiables. - Separates facts, assumptions, and fears to clarify thinking. - Maps best, base, and worst case outcomes for each option. - Evaluates reversibility and future-regret for each path. - Outputs a clear, markdown decision brief with a provisional choice or next test.
Metadata
Slug decision-forest
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Decision Forest?

Map a decision into options, non-negotiables, criteria, best/base/worst cases, reversibility, and a review checkpoint. Use when the user is comparing multipl... It is an AI Agent Skill for Claude Code / OpenClaw, with 83 downloads so far.

How do I install Decision Forest?

Run "/install decision-forest" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Decision Forest free?

Yes, Decision Forest is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Decision Forest support?

Decision Forest is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Decision Forest?

It is built and maintained by haidong (@harrylabsj); the current version is v1.0.0.

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