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golangLAKEHOUSE/reports/reality-tests/playbook_lift_002.md
root e9822f025d playbook_lift v2: paraphrase pass + run #002 finds boost-only limit 
Adds an opt-in Pass 3 to the lift driver: for each query whose Pass 1
recorded a playbook, ask the judge to rephrase the query, then re-query
with playbook=true and check whether the recorded answer surfaces in
top-K. This is the test the v1 report's caveat #3 explicitly flagged
as the actual learning-property gate (not the cheap verbatim case).

Implementation:
- New flag --with-paraphrase on the driver (default off).
- New WITH_PARAPHRASE env in the harness (default 1, on for prod runs).
- New paraphrase_* fields on queryRun + summary, // 0 fallback in jq so
  re-rendering verbatim-only evidence stays clean.
- generateParaphrase() calls the same judge model with format=json and
  a tight schema; temperature=0.5 for variance without domain drift.
- Markdown report adds a paraphrase per-query table (only when the
  pass ran) and an honesty caveat about judge-also-rephrases coupling.

Run #002 result (reports/reality-tests/playbook_lift_002.{json,md}):

  Verbatim lift               2/2 (100% — Q7 + Q13, both stable from v1)
  Paraphrase top-1            0/2
  Paraphrase any-rank in K    0/2

Both paraphrases dropped the recorded answer OUT of top-K entirely
(rank=-1). This isn't a paraphrase-quality problem — qwen2.5's outputs
preserved intent ("Hazmat-certified warehouse worker comfortable with
cold storage" → "Warehouse worker with Hazmat certification and
experience in cold storage"). It's the v0 boost-only stance documented
in internal/matrix/playbook.go:22-27: the boost only re-ranks results
that ALREADY surfaced from regular retrieval. If paraphrase's cosine
retrieval doesn't include the recorded answer in top-K, no boost can
promote it.

The "Shape B" upgrade mentioned in the playbook.go comment — inject
playbook hits directly even when they weren't in the top-K — is what
would close this gap. The reality test surfaced exactly the gap the
docs warned about. Worth filing as the next product gate.

Run-to-run variance also visible: v1 had 8 discoveries, v2 had 2.
HNSW insertion order + judge variance both contribute. Stability of
Q7 and Q13 across both runs (lifted in v1 AND v2) is the most reliable
signal in the dataset.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-30 06:47:41 -05:00

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Playbook-Lift Reality Test — Run 002

Generated: 2026-04-30T11:46:28.335370797Z Judge: qwen2.5:latest (Ollama, resolved from env JUDGE_MODEL=qwen2.5:latest) Corpora: workers,ethereal_workers Workers limit: 5000 Queries: tests/reality/playbook_lift_queries.txt (21 executed) K per pass: 10 Paraphrase pass: ENABLED Evidence: reports/reality-tests/playbook_lift_002.json

Headline

Metric Value
Total queries run 21
Cold-pass discoveries (judge-best ≠ top-1) 2
Warm-pass lifts (recorded playbook → top-1) 2
No change (judge-best already top-1, no playbook needed) 19
Playbook boosts triggered (warm pass) 2
Mean Δ top-1 distance (warm − cold) -0.011403477
Paraphrase pass — recorded answer at rank 0 (top-1) 0 / 2
Paraphrase pass — recorded answer at any rank in top-K 0 / 2

Verbatim lift rate: 2 of 2 discoveries became top-1 after warm pass.

Per-query results

# Query Cold top-1 Cold judge-best (rank/rating) Recorded? Warm top-1 Judge-best warm rank Lift
1 Forklift operator with OSHA-30, warehouse experience, day sh e-8290 0/4 — e-8290 0 no
2 OSHA-30 certified forklift operator in Wisconsin, cold stora e-2580 7/3 — e-2580 7 no
3 Production worker with confined-space cert and hazmat traini w-943 0/2 — w-943 0 no
4 CDL Class A driver, clean record, willing to do regional 4-d w-2486 0/1 — w-2486 0 no
5 Warehouse lead with current OSHA-30 certification, NOT OSHA- w-4278 2/2 — w-4278 2 no
6 Forklift-certified loader, certification must be active, dis e-3143 0/2 — e-3143 0 no
7 Hazmat-certified warehouse worker comfortable with cold stor e-898 2/4 ✓ e-665 e-665 0 YES
8 Bilingual production worker with team-lead experience and tr w-4115 0/4 — w-4115 0 no
9 Inventory specialist with confined-space cert and compliance w-1971 2/3 — w-1971 2 no
10 Warehouse worker who can run inventory cycles and lead a sma e-8132 0/4 — e-8132 0 no
11 Production line worker comfortable filling in as line superv w-2558 0/3 — w-2558 0 no
12 Customer service rep willing to cross-train into dispatch or e-1349 1/2 — e-1349 1 no
13 Reliable production line lead with strong attendance and lea e-6006 5/4 ✓ e-5778 e-5778 0 YES
14 Highly responsive forklift operator available for last-minut e-6198 0/4 — e-6198 0 no
15 Engaged warehouse associate with strong safety compliance re w-2008 0/4 — w-2008 0 no
16 CDL-A driver based in IL or WI, willing to run regional 4-da w-542 6/2 — w-542 6 no
17 Bilingual customer service rep in Indianapolis or Cincinnati e-4545 0/1 — e-4545 0 no
18 Production supervisor open to Midwest relocation for permane e-3001 7/2 — e-3001 7 no
19 Dental hygienist with three years experience, Indianapolis a e-7086 0/1 — e-7086 0 no
20 Registered nurse with ICU experience, willing to take per-di w-4936 0/1 — w-4936 0 no
21 Software engineer with React and TypeScript, three years exp w-334 0/1 — w-334 0 no

Paraphrase pass — does the playbook help similar-but-different queries?

For each query whose Pass 1 cold pass recorded a playbook entry, the judge model rephrased the query, and the rephrased version was sent through warm matrix.search. The recorded answer ID's rank in those results tests whether cosine on the embedded paraphrase finds the recorded query's vector.

# Original (≤40c) Paraphrase (≤60c) Recorded answer Paraphrase top-1 Recorded rank Paraphrase lift
7 Hazmat-certified warehouse worker comfor Warehouse worker with Hazmat certification and experience in e-665 e-4910 -1 no
13 Reliable production line lead with stron Experienced production line supervisor with excellent punctu e-5778 w-1950 -1 no

Honesty caveats

  1. Judge IS the ground truth proxy. Without human-labeled relevance, the LLM judge's verdict is what defines "best." If qwen2.5:latest rates badly, the lift number is meaningless. To validate the judge itself, sample 5–10 verdicts manually and check agreement.
  2. Score-1.0 boost = distance halved. Playbook math is distance' = distance × (1 - 0.5 × score). Lift requires the judge-best result's pre-boost distance to be ≤ 2× the cold top-1's distance, otherwise even halving doesn't promote it. Tight clusters → little visible lift.
  3. Verbatim vs paraphrase. The verbatim lift rate (above) is the cheap case — same query, recorded playbook, expected boost. The paraphrase pass (when enabled) is the actual learning property: similar-but-different queries hitting a recorded playbook. Compare verbatim and paraphrase lift rates — paraphrase should be lower (semantic-distance gates some playbook hits) but non-zero is the meaningful signal.
  4. Multi-corpus skew. Default corpora=workers,ethereal_workers — if all judge-best results land in one corpus, the matrix layer's purpose isn't being tested. Check per-corpus distribution in the JSON.
  5. Judge resolution. This run used qwen2.5:latest from env JUDGE_MODEL=qwen2.5:latest. Bumping the judge for run #N+1 means editing one line in lakehouse.toml.
  6. Paraphrase generation also uses the judge. The same model that rates relevance also rephrases queries. A judge that's bad at rating staffing queries is probably also bad at rephrasing them. Worth sanity-checking a sample of paraphrase_query values in the JSON before trusting the paraphrase lift number.

Next moves

  • If lift rate ≥ 50% of discoveries: matrix layer + playbook is doing real work. Move to paraphrase queries + tag-based boost (currently ignored).
  • If lift rate < 20%: investigate why — judge variance, distance gap too wide, or playbook math too gentle. The score=1.0 / 0.5× formula may need retuning.
  • If discovery rate (cold judge-best ≠ top-1) is itself low: cosine is already close to optimal on this query distribution. Either the corpus is too narrow or the queries are too easy.