WFGY/ProblemMap/GlobalFixMap/Eval_Observability/metrics_and_logging.md

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Eval Observability — Metrics and Logging

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A baseline schema and checklist for logging semantic metrics (ΔS, λ, coverage, E_resonance) during live runs.
Use this page to enforce consistent telemetry so that offline eval and online observability align.


Why log metrics?

  • Drift detection: High ΔS or divergent λ states catch retrieval/logic errors early.
  • Comparability: Same schema across providers, stores, and orchestration layers.
  • Debug loops: Logged traces accelerate reproduction and diagnosis.
  • Regression guards: Simple thresholds protect pipelines before release.

Core metrics to capture

Metric Definition Thresholds
ΔS(question, retrieved) Semantic distance between query and retrieved snippet Stable ≤ 0.45, Transitional 0.450.60, Risk ≥ 0.60
Coverage Fraction of gold/target section retrieved ≥ 0.70
λ_observe State of reasoning flow (→ convergent, ← divergent, <> transitional, × collapse) Must stay convergent across 3 paraphrases
E_resonance Long-window entropy of reasoning steps Should remain flat without spikes

Logging schema (JSON example)

{
  "trace_id": "uuid",
  "timestamp": "2025-08-29T12:34:56Z",
  "question": "...",
  "retrieved": [
    {
      "snippet_id": "s1",
      "section": "intro",
      "source": "docA",
      "offsets": [120, 160],
      "ΔS": 0.42
    }
  ],
  "ΔS_overall": 0.44,
  "coverage": 0.72,
  "λ_state": "→",
  "E_resonance": 0.03,
  "index_hash": "abc123",
  "dedupe_key": "sha256(...)" 
}

Quick probes

  • ΔS probe: Recompute ΔS on each retrieval call. Alert if ≥ 0.60.
  • λ probe: Run three paraphrases per eval batch, log λ_state sequence.
  • Coverage probe: Compare retrieved sections against gold or expected anchors.
  • E_resonance probe: Smooth entropy over 50100 steps, alert if spike > 2× baseline.

Storage tips

  • Write logs to append-only store (e.g., KV or time-series DB).
  • Deduplicate with dedupe_key = sha256(question + index_hash + snippet_id).
  • Keep 3090 days rolling window for regression analysis.

🔗 Quick-Start Downloads (60 sec)

Tool Link 3-Step Setup
WFGY 1.0 PDF Engine Paper 1 Download · 2 Upload to your LLM · 3 Ask “Answer using WFGY + <your question>”
TXT OS (plain-text OS) TXTOS.txt 1 Download · 2 Paste into any LLM chat · 3 Type “hello world” — OS boots instantly

Explore More

Module Description Link
WFGY Core Canonical framework entry point View
Problem Map Diagnostic map and navigation hub View
Tension Universe Experiments MVP experiment field View
Recognition Where WFGY is referenced or adopted View
AI Guide Anti-hallucination reading protocol for tools View

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