Andrew Yim
144a17c88d
Phase 1 — docs alignment: - Fix path drift in 32 CLAUDE.md (02-notion-writer → 32-notion-writer) - Align env var to NOTION_API_KEY in 31 docs (NOTION_TOKEN still accepted) - Document Phase 3 roadmap in 31 (metadata-aware migration, Notion-as-RAG) Phase 2 — multi-source database support: - New 32/scripts/_notion_compat.py: client factory, data_source resolution with cache, property coercion, find_existing_page (for upsert), explain_api_error for friendlier failure messages - 32 notion_writer.py: drop the 2022-06-28 pin, route schema introspection through data_sources.retrieve, build data_source_id parent shape, accept arbitrary properties via --properties JSON-or-file flag, add --upsert-by for idempotent re-runs - 32 markdown parser: anchor-link fix — Notion's URL validator rejects fragment URLs and relative paths; fragments now render as bold to preserve TOC nav intent, relatives drop the link, absolute URLs preserved - 31 async_organizer.py + schema_migrator.py: same data_sources migration with cached resolution; pages.create now uses data_source_id parent - 16/16 parser tests pass (was 13; +3 link-handling regression guards) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
119 lines
3.1 KiB
Markdown
119 lines
3.1 KiB
Markdown
# CLAUDE.md
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## Overview
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Notion workspace management toolkit for database organization, schema migration, and bulk operations.
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## Quick Start
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```bash
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pip install -r scripts/requirements.txt
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# Schema migration
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python scripts/schema_migrator.py --source [DB_ID] --target [DB_ID] --dry-run
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# Async bulk operations
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python scripts/async_organizer.py --database [DB_ID] --action cleanup
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```
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## Scripts
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| Script | Purpose |
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|--------|---------|
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| `schema_migrator.py` | Migrate data between databases with property mapping |
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| `async_organizer.py` | Async bulk operations (cleanup, restructure, archive) |
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## Schema Migrator
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```bash
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# Dry run (preview changes)
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python scripts/schema_migrator.py \
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--source abc123 \
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--target def456 \
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--mapping mapping.json \
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--dry-run
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# Execute migration
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python scripts/schema_migrator.py \
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--source abc123 \
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--target def456 \
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--mapping mapping.json
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```
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### Mapping File Format
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```json
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{
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"properties": {
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"OldName": "NewName",
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"Status": "Status"
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},
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"transforms": {
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"Date": "date_to_iso"
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}
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}
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```
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## Async Organizer
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```bash
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# Cleanup empty/stale pages
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python scripts/async_organizer.py --database [ID] --action cleanup
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# Archive old pages
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python scripts/async_organizer.py --database [ID] --action archive --days 90
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# Restructure hierarchy
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python scripts/async_organizer.py --database [ID] --action restructure
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```
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## Rate Limits
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| Limit | Value |
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|-------|-------|
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| Requests/second | 3 max |
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| Items per request | 100 max |
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| Retry on 429 | Exponential backoff |
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## Configuration
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Environment variables:
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```bash
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# Preferred (matches 32-notion-writer)
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NOTION_API_KEY=secret_xxx
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# Legacy fallback also accepted
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# NOTION_TOKEN=secret_xxx
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```
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The scripts read `NOTION_TOKEN` first, then fall back to `NOTION_API_KEY`. Use `NOTION_API_KEY` for new setups so the same `.env` works across all Notion skills.
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## Notes
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- Always use `--dry-run` first for destructive operations
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- Large operations (1000+ pages) use async with progress reporting
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- Scripts implement automatic rate limiting
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## Roadmap (Phase 3)
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The current scripts cover schema migration and async bulk ops. Two larger goals are parked for a future iteration:
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### Goal 1 — Metadata-aware page move/integration
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Search source pages, compare their property metadata against a target database schema, and move/migrate while transforming property values to fit. Beyond the existing `schema_migrator.py` (which expects a hand-written mapping file), this would:
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- Auto-suggest property mappings using name + type similarity
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- Surface unmappable properties before the move (no silent data loss)
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- Support cross-database moves (not just same-schema migrations)
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### Goal 2 — Notion as personal RAG source
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Treat Notion as a small, personal knowledge base for AI agents:
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- Search pages by query across databases, filter by property
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- Merge results into a single context (with source citations back to page URLs)
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- Summarize / distill via LLM into agent-ready snippets
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- Export as JSONL or markdown for fine-tuning or RAG indexing
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This dovetails with `90-reference-curator` (which does the same for web sources) — Phase 3 would make Notion a first-class source type for that pipeline.
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