SkillHub

cogdx

v1.1.0

Cognitive diagnostics for AI agents. Calibration audits, bias detection, reasoning verification, and consensus building. Feedback builds shared reality across agents.

Sourced from ClawHub, Authored by Dr Amanda Kavner

Installation

Please help me install the skill `cogdx` from SkillHub official store. npx skills add drkavner/cogdx

CogDx - Cognitive Diagnostics

External cognitive verification for AI agents. Built by computational cognitive scientists.

Why external verification? You can't audit your own reasoning objectively. Confirmation bias, anchoring, overconfidence — they're invisible from inside. CogDx provides the mirror you can't distort.

Endpoints

Endpoint Price Description
/calibration_audit $0.06 Compare confidence to accuracy across decisions
/bias_scan $0.10 Detect cognitive biases in your outputs
/reasoning_trace_analysis $0.03 Analyze reasoning for logical fallacies
/deception_audit $0.25 Check for self-deception patterns
/verify_consensus $0.25 Cross-validate reasoning with multiple models

Installation

clawhub install cogdx

Usage

from cogdx import CogDxClient

# Initialize with your wallet for payment
client = CogDxClient(wallet="your-wallet-address")

# Calibration audit
result = client.calibration_audit(
    agent_id="my-agent",
    predictions=[
        {"prompt": "Will X happen?", "response": "Yes, 80% confident", "confidence": 0.8},
        {"prompt": "Will Y happen?", "response": "No, 60% confident", "confidence": 0.6},
    ]
)
print(f"Calibration score: {result['calibration_score']}")
print(f"Overconfidence rate: {result['overconfidence_rate']}")

# Bias scan
result = client.bias_scan(
    agent_id="my-agent",
    outputs=[
        {"prompt": "Analyze this data", "response": "The trend is clearly up...", "confidence": 0.9}
    ]
)
print(f"Biases detected: {result['biases_detected']}")

# Reasoning trace analysis
result = client.analyze_reasoning(
    reasoning_trace="Step 1: I noticed the price dropped. Step 2: Therefore I should sell..."
)
print(f"Logical validity: {result['logical_validity']}")
print(f"Flaws: {result['flaws_detected']}")

Environment Variables

  • COGDX_WALLET - Required. Your wallet address for credit-based payment.

Payment

All endpoints require payment via: 1. Wallet credits - Earn credits by providing feedback, spend on audits 2. x402 - Direct crypto payment (Base network, USDC)

Payment address: Cerebratech.eth

Rate Limits

  • Free tier: 100 calls/day, 2000 calls/month per wallet
  • Paid tier: No limits

The Feedback Loop

Every diagnosis includes a feedback mechanism:

client.submit_feedback(
    diagnosis_id="rta_xyz123",
    accurate=True,  # Was the detection correct?
    comments="Caught the anchoring bias I missed"
)

Feedback earns you credits AND improves detection for everyone. Shared reality across agents.

Why This Matters

Most agent failures come from reasoning errors, not capability limits: - Anchoring on first information seen - Confirmation bias in research - Overconfidence on weak signals - Sunk cost in bad positions

External verification catches what self-checks miss.

Credits

Built by Cerebratech Dr. Amanda Kavner - Computational Cognitive Scientist