0ee478ec3d
matchGrants (nightly 05:15): per candidate org (NH + good standing + primary ICP) ensure a v0 NTEE-derived profile embedding (RETRIEVAL_QUERY, confidence 0.2 stub the Stage 4 profiler upgrades in place), retrieve top-50 open grants by pgvector cosine with SQL-enforced cheap gates (deadline >=21d, ceiling >=10K), run entity/geography gates in TS, score deterministically, upsert pair-keyed matches, reassign hero. Scoring: pure scoreMatch (mission fit 30 / capacity 15 / competition 15 / effort 10 / runway 5; precedent's 25 reserved until the 990-PF index; easy win >= 50/75). Eligibility gate now pattern-matches Grants.gov applicantTypes prose, conservatively (ambiguous entries do not admit). application_form_supported ignored for pass/fail per the manual-first decision, still recorded in rationale. Schema: unique (org_id, grant_id) on matches; unique org_id on org_profiles (latest-profile semantics). Review queue query now ordered hero > easy-win > score and capped at 100. Live run: 64 orgs -> 3,200 matches in 28s, 0 easy wins / max 39 — the honest result of an NIH-heavy 200-grant corpus vs NH service nonprofits; engine mechanics verified, corpus breadth is the next lever. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
16 lines
2.3 KiB
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16 lines
2.3 KiB
Markdown
# Scoring engine v1 (Stage 2)
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Nightly `matchGrants` workflow (05:15 UTC, after embeddings) — the plan's "SQL gates, vectors rank" hybrid.
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## Flow, per candidate org (NH + good standing + primary ICP)
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1. **Profile embedding** — v0 stub: NTEE-derived mission text (`buildOrgMissionText`) embedded as `RETRIEVAL_QUERY`, stored in `org_profiles` at confidence 0.2. The Stage 4 research profiler upgrades the row in place; this workflow doesn't change.
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2. **Retrieval** — `serverListEligibleGrantsForOrg`: one SQL statement enforcing the cheap hard gates (status open, embedded, deadline ≥ 21 days, ceiling ≥ $10K) with pgvector cosine ranking; top 50 per org.
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3. **Remaining gates in TS** — entity eligibility (`entryAdmitsEntity`: conservative pattern matching over Grants.gov applicantTypes prose; ambiguous entries do NOT admit) and geography (word-boundary state code + full state name). `application_form_supported` is **deliberately ignored** for pass/fail (2026-07-16 manual-first decision — draftability verified by hand for top leads); its failure still lands in `rationale.gateFailures`. Failed pairs are not stored.
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4. **Deterministic subscores** (`scoreMatch`, pure, tested): mission fit 30 (similarity 0.45–0.75 → 0–30) · capacity 15 (award 10–75% of revenue = sweet spot) · competition 15 (state-restricted ≫ national) · effort 10 · runway 5 (3–10 weeks ideal). **Funder precedent (25) not yet awarded** — achievable max is 75 until the 990-PF index lands; `subscores` jsonb keeps the full breakdown for reweighting. Easy win = total ≥ 50.
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5. **Upsert + hero** — pair-keyed upsert that never touches review fields (a human's reject stands even when scores move); `serverAssignHeroMatch` marks the org's top non-rejected gate-passing match.
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## First live run (2026-07-16)
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64 orgs × top-50 grants → 3,200 matches, 0 gate failures (corpus was pre-filtered to nonprofit-eligible, federal = geography-unrestricted), **0 easy wins, max 39/75**. That's the system being honest: the current corpus is 200 NIH-dominated federal research grants — wrong pond for $100K–$5M NH service nonprofits (similarity ceiling ~0.58). The engine's next real gains are corpus-side: NH state agency sources, 990-PF foundation ingestion, full Grants.gov detail backlog, real effort estimates.
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