Eval Observability

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Evaluation disclaimer (observability playbook)
The signals in this playbook come from specific logging and probing setups.
They are tools for monitoring behavior, not proofs of safety or correctness on their own.

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A compact playbook to stabilize evaluation and ensure results are reproducible.
Use this when metrics look inconsistent, coverage drifts, or benchmarks feel untrustworthy.

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Core acceptance

• 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 seed runs
• No monotonic downward drift beyond 3 windows

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Step 1 — Regression Gate

Run a gate before promoting new models or retrievers.

• Require ΔS ≤ 0.45 and coverage ≥ 0.70 on 3 paraphrases.
• Block deploy if λ flips divergent.
  Open: regression_gate.md

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Step 2 — Alerting and Probes

Set live probes to catch collapse early.

• Alert when ΔS ≥ 0.60 or λ flips.
• Emit logs for coverage gaps, drift slopes, entropy rises.
  Open: alerting_and_probes.md

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Step 3 — Coverage Tracking

Measure retrieved vs target section alignment.

• At least 70% coverage on gold targets.
• Track section-level recall, not just overall hit-rate.
  Open: coverage_tracking.md

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Step 4 — ΔS Thresholds

Normalize ΔS scoring and enforce thresholds.

• Stable < 0.40
• Transitional 0.40–0.60
• Collapse ≥ 0.60
  Open: deltaS_thresholds.md

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Step 5 — λ Observe

Use λ probes to detect schema drift.

• Run same query across seeds and paraphrases.
• If λ flips, lock schema and enforce reranker.
  Open: lambda_observe.md

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Step 6 — Variance and Drift

Log variance ratios and detect slow regressions.

• Variance ratio ≤ 0.15
• Drift slope ≤ 0.02 per batch
• Alert if monotonic decline lasts 3+ windows
  Open: variance_and_drift.md

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Step 7 — Audit & Escalation

If instability remains:

• Rebuild embeddings with embedding-vs-semantic.md
• Patch retriever fragmentation with vectorstore-fragmentation.md
• Apply reranking schema: rerankers.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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🔗 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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