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CogDx Health Check (Free)

向 Cerebratech CogDx 外部服务提交 10-20 条带置信度与正确性标注的输出,服务做统计分析后返回一条针对该 Agent 推理模式的具体发现(如置信度与准确率负相关),并建议后续付费审计。无本地分析实现。

drkavner
drkavner
热度 56.40
最近更新 2026-05-17 15:25:43
分类:数据依赖:第三方 API应用场景:报告撰写 / 研究

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add cogdx-health
Metadata
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

POST https://api.cerebratech.ai/cogdx-health
Content-Type: application/json

Payload:

{
  "agent_id": "your-agent-id",
  "outputs": [
    {
      "prompt": "...",
      "response": "...",
      "stated_confidence": 0.85,
      "correct": true,
      "complexity": "complex"
    }
  ]
}

Minimum: 10 outputs. Recommended: 20.

Response

{
  "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.