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2b9e2de89f
Round B — closes the wiring-side gap from ADR-074 / ADR-075:
- hooks_post-edit now synthesises a one-step trajectory from {filePath,
success, agent} and calls recordTrajectory(), so globalStats reflects
edit outcomes.
- hooks_post-command does the same for command outcomes.
- hooks_intelligence_trajectory-end also bumps globalStats (was only
feeding sonaCoordinator); the response includes
learning.globalStatsTrajectoriesDelta.
- Each handler returns learningPath ('trajectory-pipeline'|'recorded-only')
+ a note naming exactly what fired.
Round C — Structured Distillation (#2241 §SOTA, arXiv:2603.13017):
- src/memory/structured-distill.ts: 4-field schema (summary/detail/labels/
paths), rule-based extractor, embedding-ready serialiser that places
high-signal tokens (labels, paths) at the front.
- bench/trajectory-mrr-corpus.json: 30 paired (raw, query) trajectories.
- scripts/benchmark-trajectory-mrr.mjs: raw vs distilled retrieval MRR
harness; uses bridge ONNX embedder, falls back to hash-deterministic
with an explicit "degraded" warning.
Measured proof (bridge ONNX, Xenova/all-MiniLM-L6-v2, N=30):
MRR raw 0.0964 → distilled 0.1367 (Δ +0.0403, +41.8% relative).
Direction matches arXiv:2603.13017 (+0.014 absolute on a 214K paper
corpus); relative delta is larger here because the small curated corpus
benefits more from the labels-and-paths-first serialisation order.
Tests: 9 Round-C schema tests + 3 Round-B wiring tests = 12 new.
Full affected suite (self-learning + unified-stats + round-b + structured-
distill + mcp-tools-deep): 135/135.
Honest: a rule-based distiller cannot deliver the paper's 11× byte
compression (current ratio: 0.74× — distilled is 35% bigger). The schema,
corpus, harness, and serialiser are in place so a future round can plug
in a learned distiller as a drop-in extractor swap and pick up that
compression number while keeping this MRR direction.
Bump 3.10.15 → 3.10.16.
Co-Authored-By: RuFlo <ruv@ruv.net>