The repo has three independent SONA learn-from-feedback implementations that have drifted before:

The same stub shipped twice because nothing enforced cross-implementation behavioral parity. These scripts make "learn-from-feedback actually learns" an executable contract.

node scripts/sona-drift/harness.mjs --json        # behavioral contract matrix
node scripts/sona-drift/rvf-fingerprint.mjs        # fingerprint drift vs reference.rvf
node scripts/sona-drift/rvf-fingerprint.mjs --update   # regenerate reference (intentional change)
node scripts/sona-drift/stub-tripwire.mjs          # static no-op seam detector

Drives every implementation through one deterministic scenario (fixed probe vectors, fixed feedback embedding, fixed qualities 0.9 / 0.1 / 0.5) and checks:

• C1 fresh engine has zero adaptation
• C2 ONE positive feedback adapts — the #519/#553 regression tripwire
• C3 negative feedback also adapts (unlearning)
• C4 neutral (0.5) is a no-op — only enforced for impls that define it so (ruvllm-ts, ruvector-cli; the Rust engine intentionally applies a small quality-weighted update at 0.5, recorded but not failed)
• C5 inference output (apply/forward/route confidence) actually changes

It also extracts a 6-component behavioral fingerprint [m1-fresh, m2-1pos, m3-6pos, m4-1neg, m5-neutral, m6-inference-change]. Every component is a deterministic metric — nothing timing-based is included (durations, timestamps, throughput are inherently jittery and are excluded by construction). The harness runs each scenario twice and errors out on any bit-level difference, so jitter can never silently enter a fingerprint. The ruvllm-ts micro-LoRA is re-seeded with a fixed xorshift sequence (its production init uses Math.random()).

If npm/packages/ruvector/dist is absent or recordRouteOutcome does not exist (the #517 fix is not on main yet), ruvector-cli is reported as "skipped: ..." and does not fail the run.

Exit non-zero if any non-skipped implementation fails any contract.

Fingerprints are stored in a real RVF store (reference.rvf, dimensions=6, L2 metric) via @ruvector/rvf's native NodeBackend — one vector per implementation, id = sha256("sona-fingerprint:<impl>")[0..16]. The SDK also writes reference.rvf.idmap.json (string-id ↔ native-label sidecar); commit both files together.

Default mode re-derives current fingerprints, queries each against the stored reference vector and fails if L2 distance > max(1e-9, 1e-3 · ‖fingerprint‖). That tolerance is tight on purpose: fingerprints are deterministic, so the only legitimate distance sources are float32 quantization in the store (~1e-7 relative) and cross-platform FP reassociation in SIMD code (<1e-6 relative); real regressions move the fingerprint by >0.5 relative. If CI runs on a different platform than the one that generated the reference and this fires with a tiny distance, regenerate the reference on that platform.

Extracts each seam function body, strips comments and logging-only statements (console.*, web_sys::console, log::*!, println!, …) and fails unless at least one state-mutating statement remains (assignment, compound assignment, increment, or a non-logging call). Deliberately lenient — it catches "body is empty or only logs", not subtle bugs; the harness catches those.

1. You changed SONA learning behavior intentionally → verify the harness contract matrix still passes, then node scripts/sona-drift/rvf-fingerprint.mjs --update and commit reference.rvf + reference.rvf.idmap.json in the same PR as the behavior change. The diff of the reference is the reviewable record of the behavioral change.
2. C2/C3/C5 failed → a learn-from-feedback path stopped updating state. This is exactly the #519/#553 failure mode. Find which seam regressed (the failing impl's detail field names the API) and fix it — do NOT update the reference.
3. Tripwire fired → a seam body was reduced to comments/logging. Restore the real implementation.
4. no reference vector for id=... → a new implementation was added; run --update intentionally to enroll it.

• rvf-fingerprint.mjs --perturb (dev only) corrupts m2 in memory before validating — must exit 1.
• Harness/tripwire failure modes can be demoed against a scratch copy: copy npm/packages/ruvllm/dist/cjs to a temp dir, replace the body of processInstantLearning with a comment, then run the harness with SONA_DRIFT_RUVLLM_SONA_JS=<temp>/sona.js (C2 fails) and scanFile(<gutted .ts>, [{name:'processInstantLearning', required:true}]) from stub-tripwire.mjs (tripwire fires). Never patch the real tree.

• ruvllm-ts: harness auto-runs npm run build:cjs in npm/packages/ruvllm if dist/cjs/sona.js is missing.
• rust-sona: npm/packages/sona/index.js is committed but the platform .node binary is not; harness auto-runs npm run build there (napi build against crates/sona, needs cargo, ~40s).
• @ruvector/rvf is consumed via npm/packages/rvf/dist/database.js directly (committed) on top of the @ruvector/rvf-node platform binary resolved from the npm/ workspace node_modules. No registry fetch needed.
• Plain npm install at the workspace root fails on win32 (darwin-only optional dep); use npm install --workspaces=false if you must install.