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/BAAI__bge-reranker-v2-m3__candidate.yaml

@@ -7,6 +7,7 @@ source:
   url: https://huggingface.co/BAAI/bge-reranker-v2-m3
   revision: main
   model_card_url: https://huggingface.co/BAAI/bge-reranker-v2-m3
+  project_url: https://github.com/FlagOpen/FlagEmbedding
 license:
   spdx: Apache-2.0
   url: https://huggingface.co/BAAI/bge-reranker-v2-m3
@@ -14,6 +15,39 @@ license:
   allows_local_ops: true
   allows_fine_tune: true
   notes: "Confirm SPDX on card."
+profile:
+  summary: "Cross-encoder reranker companion to BGE-M3 for higher-precision RAG."
+  original_source: https://huggingface.co/BAAI/bge-reranker-v2-m3
+  use_cases:
+    - "Second-stage rerank of top-k chunks from BGE-M3 (or hybrid) retrieval"
+    - "Improving answer grounding for NetKingdom / ops runbook Q&A"
+    - "Eval A/B of retrieval quality without changing the generator"
+    - "Low-cost precision boost on multilingual corpora"
+  sweet_spots:
+    - "Cheap RAG quality win after a solid bi-encoder"
+    - "Small VRAM; easy always-on sidecar"
+    - "Same BAAI/FlagEmbedding family as BGE-M3"
+  not_ideal_for:
+    - "First-stage retrieval over full corpora (too slow as sole retriever)"
+    - "Generation / chat"
+    - "When latency budget forbids a second pass"
+  capability_notes: >
+    Lightweight multilingual cross-encoder from the BGE family. W-tier optional
+    after R spine; high value per byte when RAG is a primary workload.
+swot:
+  strengths:
+    - "Material precision lift for little disk/VRAM"
+    - "Proven pairing with BGE-M3"
+    - "Apache-friendly open stack"
+  weaknesses:
+    - "Cross-encoder cost scales with candidate count"
+    - "Not a substitute for better chunking or generators"
+  opportunities:
+    - "Default two-stage pipeline for lab RAG demos"
+    - "Tune candidate depth (k) per latency tier"
+  threats:
+    - "Newer BGE / open rerankers may supersede this checkpoint"
+    - "LLM-as-judge rerank experiments may reduce need for a dedicated model"
 size:
   total_bytes: 0
   total_human: "~1–2 GB (estimate)"
@@ -31,8 +65,8 @@ collection:
   storage_path: ""
   brief_refs:
     - research/2026-07-24-baseline-field-survey.md
-reason: "P1 — cheap RAG quality win as companion to BGE-M3."
-tags: [reranker, rag]
+reason: "P1/W — cheap RAG quality win as companion to BGE-M3."
+tags: [tier-w, reranker, rag]
 companions:
   - BAAI__bge-m3__candidate
 notes: ""
@@ -41,3 +75,7 @@ history:
     event: nominated
     by: baseline-survey
     detail: "P1 recommendation from initial deep research."
+  - at: "2026-07-28"
+    event: profile_swot_added
+    by: grok
+    detail: "schema 0.2 profile + SWOT."