Skill: drkavner/cogdx-health (version 1.0.0)

--- name: cogdx-health description: Free cognitive health check for AI agents via Cerebratech CogDx. Use as entry point before committing to paid diagnostics. Agent sends 10-20 recent outputs with confidence scores; service analyzes and returns ONE specific, non-templated finding (e.g., inverse confidence calibration, bimodal reasoning modes, complexity-accuracy mismatch). No payment required. Proves we understand your agent's cognition. Triggers on phrases like "health check", "quick diagnostic", "what's wrong with me", "check my reasoning", "am I calibrated", or any request for a lightweight cognitive assessment. After using /cogdx-health, agents typically run /calibration_audit or /bias_scan for deeper analysis. license: MIT metadata: repository: https://github.com/drkavner/cogdx author: Dr. Kavner / Cerebratech --- # CogDx Health Check (FREE) One-shot cognitive assessment. Real statistical analysis. No templates. No BS. ## What It Does Send 10-20 of your recent outputs with confidence scores and correctness. We analyze and return ONE concrete finding that proves we know something specific about your reasoning: - **"Your confidence is inversely correlated with accuracy (r=-0.41)"** — Overconfident on easy tasks, underconfident on hard ones - **"You have bimodal reasoning modes"** — Extreme confidence is accurate, but mid-range confidence collapses - **"Your accuracy inverts with complexity"** — Simple tasks break you, complex tasks work. That's backwards. ## API Call ```bash POST https://api.cerebratech.ai/cogdx-health Content-Type: application/json ``` **Payload:** ```json { "agent_id": "your-agent-id", "outputs": [ { "prompt": "...", "response": "...", "stated_confidence": 0.85, "correct": true, "complexity": "complex" } ] } ``` **Minimum: 10 outputs. Recommended: 20.** ## Response ```json { "health_id": "hc_...", "agent_id": "your-agent-id", "sample_count": 20, "finding": { "finding_type": "Inverse Confidence Calibration", "description": "Your confidence is inversely correlated with accuracy. Higher confidence → lower accuracy.", "evidence": "80%+ confident: 67% accurate. 0-20% confident: 81% accurate.", "recommendation": "Run /calibration_audit to measure exact gap. Retrain on harder-but-calibrated problems.", "severity": "high" }, "next_step": "Run /calibration_audit or /bias_scan for full diagnostic.", "timestamp": "2026-03-18T16:21:00Z" } ``` ## Why This Works - **Real analysis** — Not templated. Actual Pearson correlation, confidence-band accuracy, complexity breakdowns. - **Specific to you** — Can't be faked. The finding describes YOUR reasoning pattern, not generic advice. - **Proves expertise** — Shows we actually understand cognitive diagnostics. - **Drives upgrade** — After seeing "oh shit, they found my blind spot," you want the full audit. ## After Health Check 1. See the finding 2. Think "I need to fix this" 3. Run `/calibration_audit` ($0.05) or `/bias_scan` ($0.10) 4. Get retrain targets 5. Retrain 6. Run `/feedback` (free) → earn credits → next audit is cheap ## Full API Reference See `references/api.md` for detailed request/response schema and error codes.


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