Eval Observability

🏥 Quick Return to Emergency Room

You are in a specialist desk.
For full triage and doctors on duty, return here:

• WFGY Global Fix Map — main Emergency Room, 300+ structured fixes
• WFGY Problem Map 1.0 — 16 reproducible failure modes

Think of this page as a sub-room.
If you want full consultation and prescriptions, go back to the Emergency Room lobby.

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.

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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.

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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.

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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

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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

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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

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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.

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🔗 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

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Explore More

Layer	Page	What it’s for
⭐ Proof	WFGY Recognition Map	External citations, integrations, and ecosystem proof
⚙️ Engine	WFGY 1.0	Original PDF tension engine and early logic sketch (legacy reference)
⚙️ Engine	WFGY 2.0	Production tension kernel for RAG and agent systems
⚙️ Engine	WFGY 3.0	TXT based Singularity tension engine (131 S class set)
🗺️ Map	Problem Map 1.0	Flagship 16 problem RAG failure taxonomy and fix map
🗺️ Map	Problem Map 2.0	Global Debug Card for RAG and agent pipeline diagnosis
🗺️ Map	Problem Map 3.0	Global AI troubleshooting atlas and failure pattern map
🧰 App	TXT OS	.txt semantic OS with fast bootstrap
🧰 App	Blah Blah Blah	Abstract and paradox Q&A built on TXT OS
🧰 App	Blur Blur Blur	Text to image generation with semantic control
🏡 Onboarding	Starter Village	Guided entry point for new users

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