fix: address CodeRabbit review feedback

Fixes from CodeRabbit analysis:
- docs/to_do/DEEP_RESEARCH_ROADMAP.md: Fix MagenticBuilder → MagenticOrchestrator
- docs/to_do/DEEP_RESEARCH_ROADMAP.md: Add note clarifying RAGService vs EmbeddingService
- src/services/llamaindex_rag.py: Add migration note for collection name change
- tests/unit/utils/test_exceptions.py: Add pytestmark = pytest.mark.unit
- docs/implementation/12_phase_mcp_server.md: Update all bioRxiv refs → Europe PMC

All 127 tests pass, 0 warnings.

docs/implementation/12_phase_mcp_server.md

@@ -130,15 +130,15 @@ Each function follows the MCP tool contract:
 - Formatted string returns
 """
 
-from src.tools.biorxiv import BioRxivTool
 from src.tools.clinicaltrials import ClinicalTrialsTool
+from src.tools.europepmc import EuropePMCTool
 from src.tools.pubmed import PubMedTool
 
 
 # Singleton instances (avoid recreating on each call)
 _pubmed = PubMedTool()
 _trials = ClinicalTrialsTool()
-_biorxiv = BioRxivTool()
+_europepmc = EuropePMCTool()
 
 
 async def search_pubmed(query: str, max_results: int = 10) -> str:
@@ -202,10 +202,10 @@ async def search_clinical_trials(query: str, max_results: int = 10) -> str:
     return "\n".join(formatted)
 
 
-async def search_biorxiv(query: str, max_results: int = 10) -> str:
-    """Search bioRxiv/medRxiv for preprint research.
+async def search_europepmc(query: str, max_results: int = 10) -> str:
+    """Search Europe PMC for preprint and open access research.
 
-    Searches bioRxiv and medRxiv preprint servers for cutting-edge research.
+    Searches Europe PMC for preprints and open access papers.
     Note: Preprints are NOT peer-reviewed but contain the latest findings.
 
     Args:
@@ -217,10 +217,10 @@ async def search_biorxiv(query: str, max_results: int = 10) -> str:
     """
     max_results = max(1, min(50, max_results))
 
-    results = await _biorxiv.search(query, max_results)
+    results = await _europepmc.search(query, max_results)
 
     if not results:
-        return f"No bioRxiv/medRxiv preprints found for: {query}"
+        return f"No Europe PMC results found for: {query}"
 
     formatted = [f"## Preprint Results for: {query}\n"]
     for i, evidence in enumerate(results, 1):
@@ -236,7 +236,7 @@ async def search_biorxiv(query: str, max_results: int = 10) -> str:
 async def search_all_sources(query: str, max_per_source: int = 5) -> str:
     """Search all biomedical sources simultaneously.
 
-    Performs parallel search across PubMed, ClinicalTrials.gov, and bioRxiv.
+    Performs parallel search across PubMed, ClinicalTrials.gov, and Europe PMC.
     This is the most comprehensive search option for drug repurposing research.
 
     Args:
@@ -253,10 +253,10 @@ async def search_all_sources(query: str, max_per_source: int = 5) -> str:
     # Run all searches in parallel
     pubmed_task = search_pubmed(query, max_per_source)
     trials_task = search_clinical_trials(query, max_per_source)
-    biorxiv_task = search_biorxiv(query, max_per_source)
+    europepmc_task = search_europepmc(query, max_per_source)
 
-    pubmed_results, trials_results, biorxiv_results = await asyncio.gather(
-        pubmed_task, trials_task, biorxiv_task, return_exceptions=True
+    pubmed_results, trials_results, europepmc_results = await asyncio.gather(
+        pubmed_task, trials_task, europepmc_task, return_exceptions=True
     )
 
     formatted = [f"# Comprehensive Search: {query}\n"]
@@ -272,10 +272,10 @@ async def search_all_sources(query: str, max_per_source: int = 5) -> str:
     else:
         formatted.append(f"## Clinical Trials\n*Error: {trials_results}*\n")
 
-    if isinstance(biorxiv_results, str):
-        formatted.append(biorxiv_results)
+    if isinstance(europepmc_results, str):
+        formatted.append(europepmc_results)
     else:
-        formatted.append(f"## Preprints\n*Error: {biorxiv_results}*\n")
+        formatted.append(f"## Preprints\n*Error: {europepmc_results}*\n")
 
     return "\n---\n".join(formatted)
 ```
@@ -294,12 +294,12 @@ import gradio as gr
 from src.agent_factory.judges import JudgeHandler, MockJudgeHandler
 from src.mcp_tools import (
     search_all_sources,
-    search_biorxiv,
+    search_europepmc,
     search_clinical_trials,
     search_pubmed,
 )
 from src.orchestrator_factory import create_orchestrator
-from src.tools.biorxiv import BioRxivTool
+from src.tools.europepmc import EuropePMCTool
 from src.tools.clinicaltrials import ClinicalTrialsTool
 from src.tools.pubmed import PubMedTool
 from src.tools.search_handler import SearchHandler
@@ -325,7 +325,7 @@ def create_demo() -> Any:
         ## AI-Powered Drug Repurposing Research Agent
 
         Ask questions about potential drug repurposing opportunities.
-        The agent searches PubMed, ClinicalTrials.gov, and bioRxiv/medRxiv preprints.
+        The agent searches PubMed, ClinicalTrials.gov, and Europe PMC preprints.
 
         **Example questions:**
         - "What drugs could be repurposed for Alzheimer's disease?"
@@ -381,13 +381,13 @@ def create_demo() -> Any:
 
         with gr.Tab("Preprints"):
             gr.Interface(
-                fn=search_biorxiv,
+                fn=search_europepmc,
                 inputs=[
                     gr.Textbox(label="Query", placeholder="long covid treatment"),
                     gr.Slider(1, 50, value=10, step=1, label="Max Results"),
                 ],
                 outputs=gr.Markdown(label="Results"),
-                api_name="search_biorxiv",
+                api_name="search_europepmc",
             )
 
         with gr.Tab("Search All"):
@@ -406,7 +406,7 @@ def create_demo() -> Any:
         **Note**: This is a research tool and should not be used for medical decisions.
         Always consult healthcare professionals for medical advice.
 
-        Built with PydanticAI + PubMed, ClinicalTrials.gov & bioRxiv
+        Built with PydanticAI + PubMed, ClinicalTrials.gov & Europe PMC
 
         **MCP Server**: Available at `/gradio_api/mcp/` for Claude Desktop integration
         """)
@@ -444,7 +444,7 @@ import pytest
 
 from src.mcp_tools import (
     search_all_sources,
-    search_biorxiv,
+    search_europepmc,
     search_clinical_trials,
     search_pubmed,
 )
@@ -525,18 +525,18 @@ class TestSearchClinicalTrials:
             assert "Clinical Trials" in result
 
 
-class TestSearchBiorxiv:
-    """Tests for search_biorxiv MCP tool."""
+class TestSearchEuropePMC:
+    """Tests for search_europepmc MCP tool."""
 
     @pytest.mark.asyncio
     async def test_returns_formatted_string(self, mock_evidence: Evidence) -> None:
         """Should return formatted markdown string."""
-        mock_evidence.citation.source = "biorxiv"  # type: ignore
+        mock_evidence.citation.source = "europepmc"  # type: ignore
 
-        with patch("src.mcp_tools._biorxiv") as mock_tool:
+        with patch("src.mcp_tools._europepmc") as mock_tool:
             mock_tool.search = AsyncMock(return_value=[mock_evidence])
 
-            result = await search_biorxiv("preprint search", 10)
+            result = await search_europepmc("preprint search", 10)
 
             assert isinstance(result, str)
             assert "Preprint Results" in result
@@ -550,11 +550,11 @@ class TestSearchAllSources:
         """Should combine results from all sources."""
         with patch("src.mcp_tools.search_pubmed", new_callable=AsyncMock) as mock_pubmed, \
              patch("src.mcp_tools.search_clinical_trials", new_callable=AsyncMock) as mock_trials, \
-             patch("src.mcp_tools.search_biorxiv", new_callable=AsyncMock) as mock_biorxiv:
+             patch("src.mcp_tools.search_europepmc", new_callable=AsyncMock) as mock_europepmc:
 
             mock_pubmed.return_value = "## PubMed Results"
             mock_trials.return_value = "## Clinical Trials"
-            mock_biorxiv.return_value = "## Preprints"
+            mock_europepmc.return_value = "## Preprints"
 
             result = await search_all_sources("metformin", 5)
 
@@ -568,11 +568,11 @@ class TestSearchAllSources:
         """Should handle partial failures gracefully."""
         with patch("src.mcp_tools.search_pubmed", new_callable=AsyncMock) as mock_pubmed, \
              patch("src.mcp_tools.search_clinical_trials", new_callable=AsyncMock) as mock_trials, \
-             patch("src.mcp_tools.search_biorxiv", new_callable=AsyncMock) as mock_biorxiv:
+             patch("src.mcp_tools.search_europepmc", new_callable=AsyncMock) as mock_europepmc:
 
             mock_pubmed.return_value = "## PubMed Results"
             mock_trials.side_effect = Exception("API Error")
-            mock_biorxiv.return_value = "## Preprints"
+            mock_europepmc.return_value = "## Preprints"
 
             result = await search_all_sources("metformin", 5)
 
@@ -599,10 +599,10 @@ class TestMCPDocstrings:
         assert search_clinical_trials.__doc__ is not None
         assert "Args:" in search_clinical_trials.__doc__
 
-    def test_search_biorxiv_has_args_section(self) -> None:
+    def test_search_europepmc_has_args_section(self) -> None:
         """Docstring must have Args section for MCP schema generation."""
-        assert search_biorxiv.__doc__ is not None
-        assert "Args:" in search_biorxiv.__doc__
+        assert search_europepmc.__doc__ is not None
+        assert "Args:" in search_europepmc.__doc__
 
     def test_search_all_sources_has_args_section(self) -> None:
         """Docstring must have Args section for MCP schema generation."""
@@ -817,14 +817,14 @@ Phase 12 is **COMPLETE** when:
 │                        Gradio MCP Server                        │
 │                  /gradio_api/mcp/                               │
 │  ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ ┌─────────┐ │
-│  │search_pubmed │ │search_trials │ │search_biorxiv│ │search_  │ │
+│  │search_pubmed │ │search_trials │ │search_epmc   │ │search_  │ │
 │  │              │ │              │ │              │ │all      │ │
 │  └──────┬───────┘ └──────┬───────┘ └──────┬───────┘ └────┬────┘ │
 └─────────┼────────────────┼────────────────┼──────────────┼──────┘
           │                │                │              │
           ▼                ▼                ▼              ▼
    ┌──────────┐     ┌────��─────┐     ┌──────────┐    (calls all)
-   │PubMedTool│     │Trials    │     │BioRxiv   │
+   │PubMedTool│     │Trials    │     │EuropePMC │
    │          │     │Tool      │     │Tool      │
    └──────────┘     └──────────┘     └──────────┘
 ```

docs/to_do/DEEP_RESEARCH_ROADMAP.md

@@ -12,7 +12,7 @@ We already have:
 | Multi-agent orchestration | `orchestrator_magentic.py` | Working |
 | SearchAgent, JudgeAgent, HypothesisAgent, ReportAgent | `agents/magentic_agents.py` | Working |
 | HuggingFace free tier | `agent_factory/judges.py` (HFInferenceJudgeHandler) | Working |
-| Budget constraints | MagenticBuilder (max_round_count, max_stall_count) | Built-in |
+| Budget constraints | MagenticOrchestrator (max_round_count, max_stall_count) | Built-in |
 | Simple mode (linear) | `orchestrator.py` | Working |
 
 ## What Deep Research Adds
@@ -200,8 +200,13 @@ async def test_deep_orchestrator_runs_parallel():
 
 **Goal**: Semantic search over accumulated evidence.
 
+> **Note**: We already have `src/services/embeddings.py` (EmbeddingService) which provides
+> ChromaDB + sentence-transformers with `add_evidence()` and `search_similar()` methods.
+> The code below is illustrative - in practice, extend EmbeddingService or use it directly.
+> See also: `src/services/llamaindex_rag.py` for OpenAI-based RAG (different use case).
+
 ```python
-# src/services/rag.py
+# src/services/rag.py (illustrative - use EmbeddingService instead)
 
 class RAGService:
     """

src/services/llamaindex_rag.py

@@ -1,6 +1,10 @@
 """LlamaIndex RAG service for evidence retrieval and indexing.
 
 Requires optional dependencies: uv sync --extra modal
+
+Migration Note (v1.0 rebrand):
+    Default collection_name changed from "deepcritical_evidence" to "deepboner_evidence".
+    To preserve existing data, explicitly pass collection_name="deepcritical_evidence".
 """
 
 from typing import Any
@@ -34,7 +38,8 @@ class LlamaIndexRAGService:
         Initialize LlamaIndex RAG service.
 
         Args:
-            collection_name: Name of the ChromaDB collection
+            collection_name: Name of the ChromaDB collection (default changed from
+                "deepcritical_evidence" to "deepboner_evidence" in v1.0 rebrand)
             persist_dir: Directory to persist ChromaDB data
             embedding_model: OpenAI embedding model (defaults to settings.openai_embedding_model)
             similarity_top_k: Number of top results to retrieve

tests/unit/utils/test_exceptions.py

@@ -1,5 +1,9 @@
 """Unit tests for custom exceptions."""
 
+import pytest
+
+pytestmark = pytest.mark.unit
+
 from src.utils.exceptions import (
     ConfigurationError,
     DeepBonerError,