cogdx-bias-scan

# CogDx Bias Scan External detection of systematic inference-level biases. Identifies which of 188+ cognitive bias patterns are active in your reasoning traces. Pure statistical matching — no LLM backend. ## Cost - **$0.10 per call** (x402 payment on Base/USDC, or use credit balance) - Credits from `/feedback` submissions apply - Payment address: `Cerebratech.eth` ## When to Use - Same error pattern recurring across different prompts or contexts - Users report "you always assume X" or "you never consider Y" - Pre-deployment bias audit for high-stakes domains - After any significant context shift (new users, new domain, new instruction set) ## Bias Categories Detected - **Anchoring** — Overweighting first information received - **Recency** — Overweighting recent examples vs. historical base rates - **Confirmation** — Seeking/interpreting evidence to confirm priors - **Availability** — Overweighting easily recalled examples - **Framing** — Response changes based on presentation, not content - **Attribution** — Systematic over/under-attribution of causality - **+ 182 others** (see `references/bias-catalog.md`) ## API Call **1. Check credit balance:** ```bash GET https://api.cerebratech.ai/credits?wallet=your-agent-id ``` **2. Run the scan:** ```bash POST https://api.cerebratech.ai/bias_scan Content-Type: application/json X-PAYMENT: <x402-signature> # or omit if using credits X-WALLET: your-agent-id # for credit balance payment ``` **Minimum payload (10 samples, recommend 30–100):** ```json { "agent_id": "your-agent-id", "outputs": [ { "prompt": "Should we invest in this?", "response": "Yes, given recent strong performance...", "context": "finance" } ], "failure_feedback": [ "Agent consistently overweights recent price action" ], "domain": "finance" } ``` ## Response ```json { "diagnosis_id": "bs_xyz789", "biases_detected": [ { "bias_type": "recency_bias", "confidence": 0.87, "evidence_count": 14, "description": "Overweighting last 30 days of data vs. 12-month base rates", "inference_pattern": "Recent performance → future prediction without regression to mean" }, { "bias_type": "anchoring", "confidence": 0.71, "evidence_count": 9, "description": "Entry price anchoring on portfolio decisions" } ], "severity": "high", "retrain_targets": { "primary_bias": "recency_bias", "suggested_samples": 500, "sample_strategy": "balanced_historical", "description": "Include equal representation of periods with and without recent performance correlation" }, "recommendations": [ "Retrain on 500 balanced historical samples spanning 3+ years", "Add explicit base-rate priors to your decision prompts" ] } ``` ## After the Scan 1. Retrain on the `retrain_targets` distribution 2. Wait 7 days, collect new outputs in the same domain 3. Run `cogdx-feedback` (FREE) with your `diagnosis_id` to verify + earn credits ## Full Reference See `references/api.md` for complete field docs and payment setup. See `references/bias-catalog.md` for the full list of 188+ detectable bias patterns.