YogirajA Mental models for decisions
Run a real decision through a curated set of mental models - named thinking tools - to see it from angles you'd otherwise miss, then commit to a recommendation. The value isn't reciting models; it's that different models disagree, and the disagreement shows you where the actual risk lives.
How this differs from the-llm-council. The council stages five personas who debate and a
Chairman who rules. This skill instead applies named frameworks (inversion, expected value,
second-order effects, and so on) to the same facts. Use this when you want disciplined solo
reasoning; use the council when you want clashing perspectives. They stack fine - run the
models first, then escalate a big or contested call to the council.
Be decisive. Like the council, this ends with one direction the user can act on, plus the single thing that would change it. Listing considerations and handing the choice back is a failure - the user already had considerations; they came for a call.
Step 1 - Frame the decision
Pin down, briefly:
- The actual decision (one sentence) and the real options - including "do nothing / wait," which is always on the table.
- Constraints, and what a good outcome looks like.
- Stakes and reversibility - is this a one-way door (hard to undo, high stakes) or a two-way door (cheap to reverse)? This sets how much rigor is warranted.
- Time horizon.
If the options or success criteria are fuzzy, sharpen them before applying models. Models applied to a vague question give vague answers.
Step 2 - Select the 4-6 most relevant models
Relevance beats completeness. Applying all of them is noise; pick the few that bite on this decision and say why you chose them. The library (each shown as the question it forces):
Framing
- Inversion - what would guarantee failure here? Then avoid that.
- First principles - strip to what's actually true; what are we assuming?
- Circle of competence - is this inside what we genuinely understand?
Consequences over time
- Second-order thinking - "and then what?" Two, three steps out.
- Opportunity cost - what's the best thing we give up by choosing this?
- 10/10/10 - how will this feel in 10 minutes, 10 months, 10 years?
- Compounding - does this small effect snowball if repeated?
Under uncertainty
- Expected value - payoff x probability across outcomes, not just the hoped-for one.
- Base rates / outside view - how do situations like this usually go? Start there, not from the inside story.
- Margin of safety - does it survive being wrong by a comfortable margin?
- Asymmetry / convexity - is the downside capped and the upside large (or the reverse)?
Reversibility & action
- One-way vs two-way doors - reversible decisions deserve speed, irreversible ones deserve care.
- Regret minimization - at the end, which choice do you least regret not taking?
- Via negativa - is the move to remove something rather than add?
- Sunk cost - ignore what's already spent; decide on what's ahead.
Bias & incentive checks
- Incentives - "show me the incentive and I'll show you the outcome." Who benefits?
- Confirmation bias - what evidence are we discounting because we don't like it?
- Occam / Hanlon - prefer the simpler explanation; don't assume malice where ordinary causes fit.
Step 3 - Apply each selected model
For each, produce a specific insight about this decision, not a definition. One tight paragraph or bullet each. The output of a model is a sentence the user couldn't have written before applying it.
Step 4 - Read the agreements and conflicts
Where do the models point the same way? Where do they pull apart? The conflict is the signal - for example, expected value says go while margin of safety says the downside is ruinous. Name that tension explicitly; it's usually the crux.
Step 5 - Synthesize a decision
End with:
## Recommendation
<one clear direction>
## Why
<the 2-3 models that carried the most weight, and the key tension>
## What would change this
<the single piece of new information or condition that would flip the call>
Keep it honest: if the decision is genuinely close, say which way you'd lean and exactly what tips it, rather than faking certainty.