Andrew Yim
c1061dcc71
Slash command at custom-skills/31-notion-organizer/commands/notion-search.md documents the CLI surface and JSON output schema. CLAUDE.md gains a Semantic Search section explaining the 4-stage pipeline and env var requirements. requirements.txt notes the optional anthropic SDK dependency (the skill falls back to the claude CLI if missing). Final task of Phase 3b-i. 30 tests passing. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
155 lines
4.4 KiB
Markdown
155 lines
4.4 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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## Semantic Search
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```bash
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# Default browse mode (terminal table)
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python scripts/notion_search.py "AI agents in 2026"
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# JSON output for piping
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python scripts/notion_search.py "AI agents" --json | jq '.[].id'
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# Constrain to specific databases
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python scripts/notion_search.py "MCP" --databases f8f19ede-32bd-43ac-9f60-0651f6f40afe
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# Property filter
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python scripts/notion_search.py "MCP" --databases ID \
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--filter '{"Status": "Done", "Topic": "AI"}'
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# Fast mode (skip LLM stages)
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python scripts/notion_search.py "exact term" --no-rerank --no-expand
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```
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The search runs four stages:
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1. **Expand** — Claude Haiku generates up to 5 query variants (synonyms + cross-language KR↔EN)
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2. **Search** — Notion API searched per variant; results unioned + deduped at 30 candidates
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3. **Enrich** — title, properties, and 200-char excerpt fetched per candidate
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4. **Rerank** — Claude Haiku scores candidates against the *original* query; top N returned
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Results are cached for 24h (SHA256 of query + candidate IDs). Bypass with `--no-cache`.
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### Requirements
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| Env var | Purpose |
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|---------|---------|
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| `NOTION_API_KEY` (or legacy `NOTION_TOKEN`) | Notion integration token |
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| `ANTHROPIC_API_KEY` (optional) | Use Claude SDK directly. If missing, the skill falls back to `claude -p` CLI. |
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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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