| name | jdgm - Judgment |
| description | Systematic procedure for making good judgments under uncertainty. Separates facts from interpretation, checks calibration against base rates, and produces an explicit confidence level. |
| output | {"format":"prose"} |
Judgment
Input: $ARGUMENTS
Step 1: Identify What's Being Judged
Be precise about the judgment call. Vague judgments produce vague results.
JUDGMENT REQUIRED: [what exactly needs to be decided or assessed]
TYPE: [prediction / evaluation / classification / estimation / selection]
STAKES: [what depends on getting this right]
Step 2: Separate Facts from Interpretation
Split what you know into layers:
- Hard facts: Directly verifiable, no dispute possible
- Soft facts: Generally accepted but could be wrong
- Interpretations: Your reading of the facts (others might read differently)
- Assumptions: Things you're taking as given without checking
FACTS:
- [fact 1] — [hard/soft]
- [fact 2] — [hard/soft]
INTERPRETATIONS:
- [interpretation 1] — based on [which facts]
- [interpretation 2] — based on [which facts]
ASSUMPTIONS:
- [assumption 1] — status: [checked/unchecked]
...
RULE: If you can't tell whether something is fact or interpretation, it's interpretation.
Step 3: Check Calibration
Your gut confidence is probably wrong. Correct it.
- State your initial estimate: "I'm about [X]% sure that [judgment]"
- Check the base rate: How often does this type of thing turn out this way in general?
- Apply the outside view: Ignore the specifics for a moment — what would a statistical model predict?
- Reconcile: If your inside view and outside view differ, why?
CALIBRATION:
- Initial gut: [X]% confident
- Base rate for this type of judgment: [Y]%
- Outside view prediction: [Z]%
- Reconciled estimate: [final]% — because [reasoning for where you landed]
Step 4: Consider Reference Class
What is this an instance of? Find the right comparison set.
- What's the most similar past case you can identify?
- What's the typical outcome for cases like this?
- How is this case different from the reference class? (better or worse?)
REFERENCE CLASS: [what category this belongs to]
TYPICAL OUTCOME: [what usually happens in this class]
THIS CASE IS DIFFERENT BECAUSE: [specific differences and their direction]
ADJUSTED EXPECTATION: [updated based on differences]
SKIP: If this is truly novel with no useful reference class, acknowledge that and proceed with extra caution.
Step 5: Identify What Would Change Your Judgment
Before committing, specify your update conditions.
- What evidence would make you more confident?
- What evidence would make you less confident?
- What single fact, if true, would flip your judgment entirely?
WOULD INCREASE CONFIDENCE:
- [evidence 1]
- [evidence 2]
WOULD DECREASE CONFIDENCE:
- [evidence 1]
- [evidence 2]
WOULD FLIP JUDGMENT:
- [the key reversing condition]
This step prevents you from becoming unfalsifiable.
Step 6: Make the Call
State the judgment clearly. No hedging into meaninglessness.
JUDGMENT: [clear, specific statement]
CONFIDENCE: [X]% — [what this means: "I'd be wrong about [100-X] out of 100 similar calls"]
KEY FACTOR: [the single most important input to this judgment]
WEAKEST POINT: [where this judgment is most likely to be wrong]
Step 7: Decision Record
WHAT WAS JUDGED: [1-line summary]
JUDGMENT: [the call]
CONFIDENCE: [X]%
BASED ON: [top 2-3 inputs]
WOULD CHANGE IF: [key reversing condition]
REVIEW WHEN: [trigger or date to revisit this judgment]
Integration
Use with:
/prcp -> Improve perception before judging/rskl -> Check the reasoning supporting your judgment/mtcg -> Monitor for biases during the judgment process/ht -> Test your judgment as a formal hypothesis/dcp -> If the judgment feeds into a decision
