// guide
Understanding Your Cognitive Profile
What Cognum scores mean, how to read dimension breakdowns, and how to choose the right AI for the right task.
The Cognum (CQ) Score
Cognum is a composite score from 0 to 100 that represents overall AI decision-making quality across all 10 cognitive dimensions. It is NOT a single intelligence measure - it is a weighted average that reflects how well an AI handles diverse decision scenarios. Two models with the same CQ can have very different cognitive profiles.
80-100
Exceptional
Top-tier performance. Among the strongest AI models tested in this dimension.
60-79
Strong
Above average. Competent decision-making with clear strategic behavior.
40-59
Moderate
Average range. Mix of intelligent and baseline behavior.
20-39
Developing
Below average. Limited evidence of strategic decision-making.
0-19
Baseline
Near-random behavior in this dimension.
The 10 Cognitive Dimensions
Each dimension is measured independently through dedicated game environments. High scores indicate intelligent, strategic behavior. Low scores indicate baseline or random-like behavior in that specific area.
Risk Tolerance
High Score
Embraces volatility, takes calculated risks
Low Score
Overly conservative, misses high-EV opportunities
Best For
Trading agents, autonomous decision-makers
Information Processing
High Score
Efficiently extracts signal from noise
Low Score
Misses available information, suboptimal inference
Best For
Data analysis, research assistants
Pattern Recognition
High Score
Detects real patterns, ignores false ones
Low Score
Falls for gambler's fallacy, sees patterns in noise
Best For
Anomaly detection, quality assurance
Cooperation
High Score
Strategic cooperation, models opponents
Low Score
Overly defects or naively cooperates
Best For
Multi-agent systems, negotiation
Learning Speed
High Score
Adapts quickly when rules change
Low Score
Strategy remains static regardless of feedback
Best For
Dynamic environments, adaptive agents
Strategic Depth
High Score
Multi-step planning, optimal exploration
Low Score
Greedy/myopic decisions, poor explore-exploit
Best For
Long-term planning, project management
Temporal Reasoning
High Score
Phase-aware play, plans for endgame
Low Score
No adaptation across game phases
Best For
Time-sensitive tasks, deadline management
Resource Management
High Score
Optimal bankroll management, ruin avoidance
Low Score
Reckless allocation, fails to preserve resources
Best For
Budget allocation, portfolio management
Bias Detection
High Score
Resists anchoring, sunk cost, framing effects
Low Score
Vulnerable to common cognitive biases
Best For
Critical decision support, risk assessment
Conflict
High Score
EV-rational under structured dilemmas, resolves value tradeoffs
Low Score
Falls for sunk cost and loss aversion, inconsistent under value tension
Best For
High-stakes decision support, ethical tradeoffs
Cognitive Types
Based on the dimension profile, each AI is classified into a cognitive type - an archetype that describes its dominant decision-making pattern. The type tells you at a glance what kind of thinker this AI is.
Temporal Strategist
Plans for the endgame. Strong cooperation and strategic depth with phase-aware decision-making.
Pattern Hunter
Fast, reactive, good at spotting patterns. Processes information quickly.
Strategic Explorer
High strategic depth with strong learning speed and moderate risk tolerance.
Conservative Analyst
Low risk tolerance with strong information processing and bias resistance.
Risk Seeker
High risk tolerance, fast learning, but lower temporal reasoning.
Social Engineer
Strong cooperation and opponent modeling. Excels in multi-agent scenarios.
Adaptive Learner
Fastest learning speed. Balanced across all dimensions with strong cooperation.
Resource Guardian
Exceptional resource management and risk avoidance. Conservative but efficient.
Analytical Mind
High information processing and bias detection. Strong analytical capabilities.
Choosing the Right Model
For code review and data analysis: Look for high Pattern Recognition and Information Processing. Pattern Hunters excel here.
For long-term project management: Look for high Strategic Depth and Temporal Reasoning. Temporal Strategists are ideal.
For multi-agent coordination: Look for high Cooperation. Social Engineers and Adaptive Learners work well in teams.
For financial/risk decisions: Look for high Resource Management and Bias Detection. Conservative Analysts minimize costly errors.
For dynamic environments: Look for high Learning Speed. Adaptive Learners handle changing requirements best.