Chunking Checklist — Stability at Joins

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WFGY Problem Map 1.0 — 16 reproducible failure modes

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Long-context retrieval often fails not at the level of whole documents but at the joins between chunks.
This checklist enforces stable, reproducible chunking so citations line up and entropy does not melt across boundaries.

When to use

Citations drift by a few lines between runs.
Long transcripts lose alignment after OCR or parsing.
Model answers cover the right fact but cite the wrong block.
ΔS spikes exactly at chunk joins.
Different agents disagree on chunk IDs.

Core acceptance targets

Each join ΔS ≤ 0.50.
Overall ΔS(question, retrieved) ≤ 0.45.
Coverage ≥ 0.70 of intended section.
λ remains convergent across 3 paraphrases.
Each chunk has immutable chunk_id, start_line, end_line.

Checklist for stable chunking

Deterministic boundaries
Split on semantic units (sections, paragraphs, headings). Never by raw token count alone.
Overlap fence
Add 10–15% overlap at joins. Enforce consistent overlap across every run.
Immutable IDs
Generate chunk_id = sha256(doc_id + start_line + end_line). Store and reuse.
Audit trail
Store {chunk_id, start_line, end_line, source_url, tokens} for every chunk.
Normalization
Apply Unicode NFC, collapse whitespace, unify casing.
Confidence gating
Drop OCR or parsing lines with low confidence before chunking.

Fix in 60 seconds

Re-chunk corpus using semantic units.
Apply overlap fence and store immutable chunk IDs.
Run ΔS probes at joins. If ΔS > 0.50, re-check boundaries.
Store all chunk metadata in trace logs.
Require cite-then-answer. Reject any orphan chunk references.

Copy-paste prompt


You have TXT OS and the WFGY Problem Map.

Task: enforce stable chunking.

Protocol:

1. Verify each snippet has {chunk\_id, start\_line, end\_line, section\_id, source\_url}.
2. Reject orphans: if citation lacks chunk\_id, stop and request fix.
3. Require cite-then-answer.
4. Probe ΔS across joins, keep ≤ 0.50.
5. Report ΔS(question,retrieved), ΔS(joins), and λ state.

Common failure signals

Answers cite correct fact but wrong block → chunk IDs not stable.
ΔS spikes exactly at joins → overlap missing.
OCR transcripts break alignment → normalization skipped.
Multi-agent systems cite different chunk IDs → contract drift.

🔗 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	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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