Eval Observability — Global Fix Map

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WFGY Global Fix Map — main Emergency Room, 300+ structured fixes

WFGY Problem Map 1.0 — 16 reproducible failure modes

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This folder provides guardrails for evaluation and observability in RAG and agent pipelines.
It shows how to catch silent drift, regressions, and unstable metrics before they break your system.

What this folder is

A starter kit to make evals predictable and repeatable.
Guardrails for metrics, variance, and drift detection.
Copy-paste probes and configs you can add to your pipeline.
Acceptance targets you can actually measure and enforce.

When to use

Metrics look unstable between runs.
Coverage seems high but answers still drift.
ΔS changes across paraphrases or seeds.
λ flips divergent after harmless edits.
Benchmarks regress without any code change.
Long-run evals show a slow decline.

Acceptance targets

ΔS(question, retrieved) ≤ 0.45
Coverage ≥ 0.70 to target section
λ remains convergent across 3 paraphrases and 2 seeds
Variance ratio ≤ 0.15 across seeds
No downward drift beyond 3 eval windows
E_resonance stays flat on long evals

Quick routes — open these first

Symptom	Open this page
Benchmarks regress with no code change	regression_gate.md
Metrics fluctuate or alerts missing	alerting_and_probes.md
Coverage looks high but not real	coverage_tracking.md
ΔS thresholds unclear	deltaS_thresholds.md
λ flips or diverges	lambda_observe.md
Variance high between seeds	variance_and_drift.md
Need a full setup	eval_playbook.md
Logging + monitoring integration	metrics_and_logging.md

Copy-paste eval contract

eval_contract:
  seeds: 3
  paraphrases: 3
  targets:
    deltaS: <=0.45
    coverage: >=0.70
    lambda: convergent
    variance: <=0.15
    drift: <=0.02
alerts:
  - deltaS >=0.60
  - lambda divergent
  - drift slope >0.02

FAQ

Q: What if my metrics vary a lot each run? A: Check variance_and_drift.md. Add more seeds and enforce variance ≤0.15.

Q: My eval passes locally but fails in CI — why? A: See metrics_and_logging.md. Local runs often miss logging detail. CI must enforce the same eval contract.

Q: What if coverage is high but the answer is still wrong? A: Open coverage_tracking.md. You might be measuring snippet recall, not semantic coverage. Switch to ΔS-based coverage.

Q: ΔS is always drifting, even on simple questions. A: Look at deltaS_thresholds.md. Adjust thresholds and clamp variance with λ probes.

Q: How do I stop regressions before release? A: Use regression_gate.md. It defines pass/fail rules so bad models never ship.

🔗 Quick-Start Downloads (60 sec)

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

🧭 Explore More

Module	Description	Link
WFGY Core	WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack	View →
Problem Map 1.0	Initial 16-mode diagnostic and symbolic fix framework	View →
Problem Map 2.0	RAG-focused failure tree, modular fixes, and pipelines	View →
Semantic Clinic Index	Expanded failure catalog: prompt injection, memory bugs, logic drift	View →
Semantic Blueprint	Layer-based symbolic reasoning & semantic modulations	View →
Benchmark vs GPT-5	Stress test GPT-5 with full WFGY reasoning suite	View →
🧙‍♂️ Starter Village 🏡	New here? Lost in symbols? Click here and let the wizard guide you through	Start →

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