v0.1.3 — attestation fail-close and registry/teacher robustness

Highlights

• Training CI fail-closes forged attestation (#194): NRAS JWKS + claim binding (+ TDX when present/required) before eval tiers.
• Registry / export / teacher hardening (#195): no crash on bad prior registry rows; LF+UTF-8 sha pins; skip flaky teacher calls.
• Package version 0.1.3 (pyproject was still 0.1.1 after the v0.1.2 tag).
• Pairs with SparkProof v0.1.3 — Sol→Fable CoT recovery for better training datasets (details below).

SparkProof Sol→Fable CoT recovery (better training data)

SparkDistill students learn from SparkProof trajectories that wrap teacher reasoning in <think>…</think> before the verified Triton answer. GPT 5.6 Sol often returns only encrypted reasoning_details, so a Sol best-of-N win previously produced a verified kernel without a usable chain-of-thought for SFT.

SparkProof v0.1.3 (#31) fixes that for dataset miners:

1. Best-of-N unchanged — still calls Claude Fable 5 + GPT 5.6 Sol, validates on Blackwell/Hopper, keeps the higher-scoring winner.
2. When Sol wins with encrypted/empty CoT — SparkProof calls Fable again:
   • Re-solve (preferred): Fable gets Sol’s verified kernel as a hint, produces its own full answer + plaintext engineering rationale, then re-validates on GPU. If it passes, that Fable trajectory is kept (metadata.cot_recovery=fable_resolve).
   • Explain (fallback): if re-solve fails validation, Fable writes an inspectable rationale while Sol’s gold verified code stays the assistant answer (metadata.cot_recovery=fable_explain).
3. SFT export — skips encrypted reasoning JSON dumps so <think> tags stay useful; prefers the original mining-task prompt (prompt_meta.prompt) as the user turn.

What this is / isn’t: this does not decrypt Sol’s private CoT. It produces Fable-authored, train-able rationales bound to hardware-verified kernels — aligned with SparkProof’s preference for inspectable engineering rationale over opaque encrypted traces.

Why it matters for SparkDistill: registry / canonical mining mixes built with SparkProof ≥ v0.1.3 should yield more rows with real <think> traces when Sol would otherwise have won “code-only,” improving distillation quality on Triton reasoning without weakening GPU validation or attestation.

Miners: upgrade SparkProof to v0.1.3 before the next dataset generation pass.

Also in this release

• Unattested training PRs cannot earn eval tiers.
• Repair-tier mix dedupe matches SparkProof task-prompt fingerprints.
• Dataset registry gate: clean dataset:REJECT on malformed prior rows / invalid JSON (no CI traceback).
• GPU corroboration uses hwmodel claims only (#149).

Full notes: see CHANGELOG.