feat(reference-curator): implement Python scripts + Gemini quality gate

Build the refcurator shared Python package and 7 CLI scripts that were
previously specification-only. Add Gemini CLI as an independent pre-distillation
quality evaluator, replacing the circular Claude-self-review pattern.

Key changes:
- shared/lib/src/refcurator/: 7-module package (config, db, models, utils,
  manifest, gemini) with PyMySQL + JSON file dual backend
- 7 Click CLI scripts: discover, crawl_mgr, repo, distiller, reviewer,
  exporter, pipeline — each with subcommands for data management
- Gemini quality gate: evaluates raw content BEFORE distillation using
  5 criteria (relevance, authority, completeness, freshness, distill_value)
- Pipeline reordered: discovery → crawl → store → evaluate → distill → export
- Bug fixes from Codex adversarial review:
  - FileBackend now hard-fails on JOIN/aggregate/GROUP BY queries
  - Exporter uses MAX(review_id) to prevent shipping stale approvals
  - Distiller updates existing rows on refactor instead of forking
- Updated all 7 CLAUDE.md directives with real script references
- install.sh updated with refcurator package install step

51/51 E2E tests passing.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

custom-skills/90-reference-curator/06-markdown-exporter/code/CLAUDE.md

@@ -9,57 +9,51 @@ Exports approved reference content as structured markdown files for project know
 
 | Type | Format | Use Case |
 |------|--------|----------|
-| `project_files` | Nested markdown | Claude Projects knowledge |
-| `fine_tuning` | JSONL | Model fine-tuning dataset |
-| `knowledge_base` | Flat markdown | Documentation |
+| `project` | Nested markdown | Claude Projects knowledge |
+| `finetuning` | JSONL | Model fine-tuning dataset |
 
 ## Workflow
 
-### Step 1: Query Approved Content
+### Step 1: Export Project Files
 ```bash
-python scripts/query_approved.py --min-score 0.80 --output approved.json
+uv run python scripts/exporter.py project \
+  --output ~/reference-library/exports/ \
+  --min-score 0.80 \
+  --structure nested_by_topic
 ```
 
-### Step 2: Organize by Structure
-
-**Nested by Topic (default):**
+Output structure:
 ```
 exports/
 ├── INDEX.md
 ├── prompt-engineering/
 │   ├── _index.md
-│   ├── 01-chain-of-thought.md
-│   └── 02-few-shot-prompting.md
+│   ├── 00-chain-of-thought.md
+│   └── 01-few-shot-prompting.md
 └── claude-models/
     ├── _index.md
-    └── 01-model-comparison.md
+    └── 00-model-comparison.md
 ```
 
-**Flat Structure:**
-```
-exports/
-├── INDEX.md
-├── prompt-engineering-chain-of-thought.md
-└── claude-models-comparison.md
-```
-
-### Step 3: Generate Files
+### Step 2: Generate INDEX
 ```bash
-python scripts/export_project.py \
-  --structure nested_by_topic \
-  --output ~/reference-library/exports/ \
-  --include-metadata
+uv run python scripts/exporter.py index --output ~/reference-library/exports/INDEX.md
 ```
 
-### Step 4: Generate INDEX
+### Step 3: Add Cross-References
 ```bash
-python scripts/generate_index.py --output ~/reference-library/exports/INDEX.md
+uv run python scripts/exporter.py crossrefs --input ~/reference-library/exports/
+```
+
+### Step 4: Verify Export
+```bash
+uv run python scripts/exporter.py verify --path ~/reference-library/exports/
 ```
 
 ### Step 5: Fine-tuning Export (Optional)
 ```bash
-python scripts/export_finetuning.py \
-  --output ~/reference-library/exports/fine_tuning.jsonl \
+uv run python scripts/exporter.py finetuning \
+  --output ~/reference-library/exports/training.jsonl \
   --max-tokens 4096
 ```
 
@@ -71,62 +65,25 @@ JSONL format:
     {"role": "user", "content": "Explain {title}"},
     {"role": "assistant", "content": "{structured_content}"}
   ],
-  "metadata": {"source": "{url}", "topic": "{topic_slug}", "quality_score": 0.92}
+  "metadata": {"source": "{url}", "quality_score": 0.92}
 }
 ```
 
 ### Step 6: Log Export Job
 ```bash
-python scripts/log_export.py --name "January 2025 Export" --type project_files --docs 45
-```
-
-## Cross-Reference Generation
-```bash
-python scripts/add_crossrefs.py --input ~/reference-library/exports/
-```
-
-Links related documents based on overlapping key concepts.
-
-## Output Verification
-
-After export, verify:
-- [ ] All files readable and valid markdown
-- [ ] INDEX.md links resolve correctly
-- [ ] No broken cross-references
-- [ ] Total token count matches expectation
-- [ ] No duplicate content
-
-```bash
-python scripts/verify_export.py --path ~/reference-library/exports/
+uv run python scripts/exporter.py log --name "April 2026 Export" --type project_files --docs 45
 ```
 
 ## Scripts
 
-- `scripts/query_approved.py` - Get approved content from DB
-- `scripts/export_project.py` - Main export for project files
-- `scripts/export_finetuning.py` - JSONL export for fine-tuning
-- `scripts/generate_index.py` - Generate INDEX.md
-- `scripts/add_crossrefs.py` - Add cross-references
-- `scripts/log_export.py` - Log export job to DB
-- `scripts/verify_export.py` - Verify export integrity
-
-## Configuration
-
-```yaml
-# ~/.config/reference-curator/export_config.yaml
-output:
-  base_path: ~/reference-library/exports/
-  project_files:
-    structure: nested_by_topic
-    index_file: INDEX.md
-    include_metadata: true
-  fine_tuning:
-    format: jsonl
-    max_tokens_per_sample: 4096
-
-quality:
-  min_score_for_export: 0.80
-```
+| Command | Purpose |
+|---------|---------|
+| `exporter.py project` | Export as nested markdown files |
+| `exporter.py finetuning` | Export as JSONL training dataset |
+| `exporter.py index` | Generate INDEX.md table of contents |
+| `exporter.py crossrefs` | Add cross-reference links |
+| `exporter.py verify` | Verify export integrity |
+| `exporter.py log` | Log export job to DB |
 
 ## Integration