Register reserve under agents hub and pin VAULT storage.

Classify freedom-intelligence for State Hub (agents domain), sync FI-WP-0001..0003 with hub IDs, enrich catalog entries with profile/SWOT, and pin the open-weight reserve to D:\vault\coulomb\freedom-intelligence\ with strategic S-tier policy.

inventory/catalog/nomic-ai__nomic-embed-text-v1.5__candidate.yaml

@@ -7,6 +7,7 @@ source:
   url: https://huggingface.co/nomic-ai/nomic-embed-text-v1.5
   revision: main
   model_card_url: https://huggingface.co/nomic-ai/nomic-embed-text-v1.5
+  project_url: https://www.nomic.ai/
 license:
   spdx: Apache-2.0
   url: https://huggingface.co/nomic-ai/nomic-embed-text-v1.5
@@ -14,6 +15,39 @@ license:
   allows_local_ops: true
   allows_fine_tune: true
   notes: ""
+profile:
+  summary: "Lightweight open text embedder for A/B with BGE-M3 and long-context retrieval experiments."
+  original_source: https://huggingface.co/nomic-ai/nomic-embed-text-v1.5
+  use_cases:
+    - "Secondary / A/B embedding path vs BGE-M3"
+    - "English-heavy RAG with low resource cost"
+    - "Long-context embedding experiments (per card capabilities)"
+    - "Portable laptop offline search indexes"
+  sweet_spots:
+    - "Small footprint Apache embed"
+    - "Fast iteration when re-embedding corpora often"
+    - "Nomic tooling and Matryoshka-style dimension flexibility (per card)"
+  not_ideal_for:
+    - "Sole multilingual production embed without A/B (prefer BGE-M3 default)"
+    - "Generation tasks"
+    - "Code-only retrieval (prefer code embed if held)"
+  capability_notes: >
+    Compact Nomic text embedding model. Held as runnable dual-path to avoid
+    single-vendor embed lock-in and to re-eval retrieval quality cheaply.
+    Prefer current v2 text card at pull if clearly better.
+swot:
+  strengths:
+    - "Tiny, Apache-2.0, easy to re-run indexes"
+    - "Diversifies embed dependency next to BGE-M3"
+  weaknesses:
+    - "May lose multilingual or domain A/B vs BGE-M3"
+    - "Version churn (v1.5 vs v2) needs careful pin"
+  opportunities:
+    - "Dimension-reduced storage for large corpora"
+    - "Hybrid ensembles (BGE + nomic signals)"
+  threats:
+    - "Becomes redundant if one embed wins all lab evals"
+    - "Upstream rename/deprecation of v1.5"
 size:
   total_bytes: 0
   total_human: "<1 GB"
@@ -31,12 +65,17 @@ collection:
   storage_path: ""
   brief_refs:
     - research/2026-07-24-baseline-field-survey.md
-reason: "P0 lightweight embed for A/B with BGE-M3; long-context text retrieval."
-tags: [embedding, rag]
-companions: []
+reason: "P0/R lightweight embed for A/B with BGE-M3; long-context text retrieval."
+tags: [tier-r, embedding, rag]
+companions:
+  - BAAI__bge-m3__candidate
 notes: "If v2 text is preferred at collection time, update id/url and supersede this candidate."
 history:
   - at: "2026-07-24"
     event: nominated
     by: baseline-survey
     detail: "P0 recommendation from initial deep research."
+  - at: "2026-07-24"
+    event: profile_swot_added
+    by: grok
+    detail: "schema 0.2 profile + SWOT."