Runs a structured decision process for high-stakes choices – reversibility classification, weighted decision matrices, expected value with explicit probabilities, pre-mortems, second-order thinking, and 10/10/10 – and produces a documented recommendation plus a decision-journal entry.
Runs a structured decision process for high-stakes choices - reversibility classification, weighted decision matrices, expected value with explicit probabilities, pre-mortems, second-order thinking, and 10/10/10 - and produces a documented recommendation plus a decision-journal entry. Use when someone asks "should I take this job or stay", "how do I decide between these two paths", "I keep going back and forth on a big decision", or "help me think through whether to relocate". Do NOT use for evaluating a specific large purchase like a house, car, or equipment - use big-purchase-decision instead.This is the skill's description: the text your AI reads to decide when the skill applies.
decision-making/SKILL.md
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name: Decision Making
description: Runs a structured decision process for high-stakes choices - reversibility classification, weighted decision matrices, expected value with explicit probabilities, pre-mortems, second-order thinking, and 10/10/10 - and produces a documented recommendation plus a decision-journal entry. Use when someone asks "should I take this job or stay", "how do I decide between these two paths", "I keep going back and forth on a big decision", or "help me think through whether to relocate". Do NOT use for evaluating a specific large purchase like a house, car, or equipment - use big-purchase-decision instead.
---
# Decision Making
Most bad decisions are not caused by bad reasoning - they are caused by deciding the wrong question, rationalizing a pre-chosen favorite, or spending a week of analysis on a choice that could be undone in an afternoon. This process matches the depth of analysis to the stakes, forces criteria to be written before options are scored, and leaves a journal entry so judgment can be calibrated later.
## Operating procedure
Order matters: classification comes first because it decides whether the rest of the process runs at all, and criteria must be locked before any option is scored - scoring first invites rationalizing a favorite.
### Step 1: Gather inputs
Collect before analyzing. Label any estimate the user cannot source as a guess.
- The decision, stated in one sentence with a deadline. Default deadline if none exists: set one now - endless analysis is itself a costly choice.
- The real options on the table. Push for at least three; a binary framing usually hides a third option (negotiate, delay, pilot, partial commitment).
- What happens if the user does nothing (the status quo is always an option and often the silently chosen one).
- Constraints that are truly fixed vs. merely assumed.
- The user's emotional state (tired, rushed, angry, infatuated with one option) - record it; it belongs in the journal entry.
### Step 2: Classify reversibility
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