critical-thinking-logical-reasoning

name	critical-thinking-logical-reasoning
description	Surface hidden assumptions, detect logical fallacies, examine evidence quality, and stress-test arguments before committing to them.
group	thinking
keywords	["critical-thinking","logical-reasoning","fallacies","assumptions","evidence","argument","analysis","reasoning"]
task_strategies	["spike","investigation"]
stream_affinity	["roadmap","research"]
allowed-tools	["Read","Glob","Grep","AskUserQuestion"]
status	experimental
source	Richard Paul & Linda Elder — Critical Thinking (2006); Kahneman — Thinking Fast and Slow (2011); Aristotle — Prior Analytics
acquired	2026-06-15

Critical Thinking & Logical Reasoning

Find what's wrong with the argument before you commit to it.

Critical thinking is not skepticism for its own sake — it's the discipline of examining the quality of reasoning before acting on it. The goal is to catch flawed logic, hidden assumptions, and weak evidence before they become expensive decisions.

---

When to use

• Evaluating a proposal, plan, or recommendation
• When an argument sounds compelling but feels off
• Before accepting data-driven claims
• When debugging a persistent wrong belief in a team
• After research — to evaluate what you found before applying it
• Pairs with /brana:challenge for adversarial review; /brana:first-principles for rebuilding from what's actually true

---

Step 1 — Identify the claim

What is being asserted?

AskUserQuestion: "What claim, argument, or reasoning are we examining?"

State it in the clearest possible form. Often the act of stating a claim precisely already reveals its weakness.

---

Step 2 — Surface hidden assumptions

Every argument rests on assumptions. List them all:

Existential assumptions — "X exists" or "X is real"

• Example: "Our users are power users" assumes that power users are a significant segment

Causal assumptions — "X causes Y"

• Example: "More features = more retention" assumes features are the bottleneck for retention

Comparative assumptions — "X is better than Y"

• Example: "Rewriting will be faster" assumes the rewrite won't hit the same problems

Scoping assumptions — "This applies to all of / most of / some of X"

• Example: "Users want this" means... how many? Which users?

For each assumption:

• Is it stated or hidden?
• What evidence supports it?
• What would change if it's wrong?

---

Step 3 — Examine evidence quality

For each claim, ask:

Question	What to look for
Source	Primary source or hearsay? Who funded the research?
Sample	How big? How representative? Self-selected?
Method	Controlled? Correlation confused for causation?
Recency	Is this still true? Context may have changed
Completeness	What evidence AGAINST the claim exists?

Evidence strength scale:

• Strong: large controlled study, multiple independent replications
• Moderate: single study, observational data, expert consensus
• Weak: anecdote, single data point, self-report, authority claim
• None: assertion without evidence

---

Step 4 — Check for logical fallacies

Common fallacies in technical and business reasoning:

Fallacy	Pattern	Example
Ad hominem	Attack the person, not the argument	"Of course they'd say that, they're from [company]"
Appeal to authority	Authority = truth	"Google does it this way"
False dichotomy	Only two options	"We either rewrite or stay stuck forever"
Slippery slope	One step inevitably leads to extreme	"If we add this exception, everything will become exceptions"
Strawman	Misrepresent the opposing view	"So you're saying we should never refactor?"
Correlation/causation	A happens with B, therefore A causes B	"Users who use feature X retain better, so feature X causes retention"
Sunk cost	Past investment justifies future investment	"We've already spent 3 months on this"
Availability heuristic	Recent/memorable = common	"I've seen this bug before so it must be frequent"
Confirmation bias	Seeking evidence that confirms, ignoring disconfirming	Only citing studies that support the conclusion
Base rate neglect	Ignoring prior probability	"Our competitor failed at this but we're better"

Mark each fallacy found: [claim] → [fallacy type] → [why it's wrong here]

---

Step 5 — Evaluate the argument structure

Is the reasoning valid? (Does the conclusion follow from the premises?) Is the reasoning sound? (Are the premises true AND does the conclusion follow?)

Premise 1: [X]
Premise 2: [Y]
∴ Conclusion: [Z]

Valid? [yes/no] — does Z follow from X and Y?
Sound? [yes/no] — are X and Y actually true?

An argument can be valid (correct structure) but unsound (false premises). Most flawed reasoning is unsound, not invalid.

---

Step 6 — Output

**Critical thinking analysis of [claim/argument]**

Core claim: [restated precisely]

Hidden assumptions found: [N]
  Critical: [most load-bearing assumption]
  Status: [supported/unsupported/false]

Evidence quality: [strong/moderate/weak/none]
  Key gap: [what evidence is missing]

Fallacies detected: [list]

Argument structure: [valid/invalid] + [sound/unsound]

Verdict:
  Accept as is / Accept with caveats / Reject / Needs more evidence
  Key condition: [what would change the verdict]

---

Notes

• The goal is not to win arguments — it's to make better decisions by reasoning better
• Steel-man before attacking: state the strongest version of the opposing argument first
• Kahneman's System 1/System 2: most reasoning errors come from System 1 (fast, intuitive) presenting conclusions to System 2 (slow, analytical) without flagging they're conclusions
• "I believe X" is not the same as "there is evidence for X" — distinguish confidence from evidence
• Strong critical thinking produces "I was wrong" as often as "they're wrong"
• Pair with /brana:brainstorm after debunking — critique clears the space; brainstorm fills it