migrate
Universal migration from Obsidian, Notion, Logseq, markdown, CSV, JSON, Roam
Skill by ltdrew
Chalk Labs
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/ltdrew-migrate
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: documents, spreadsheets, productivity
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What's inside
- Skill name
migrate- Description
- Universal migration from Obsidian, Notion, Logseq, markdown, CSV, JSON, Roam
- License
- MIT
- Instructions
- 122 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Migrate Skill Universal migration from any wiki, note tool, or brain system into GBrain. ## Contract - Source data is never modified or deleted; migration is additive only. - Every migrated page is verified round-trip: written to gbrain, read back, spot-checked. - Cross-references from the source system (wikilinks, block refs, tags) are converted to gbrain equivalents. - Migration is tested on a sample (5-10 files) before bulk execution. - Post-migration health check confirms page count, link integrity, and embedding coverage. ## Supported Sources | Source | Format | Strategy | |--------|--------|----------| | Obsidian | Markdown + `[[wikilinks]]` | Direct import, convert wikilinks to gbrain links | | Notion | Exported markdown or CSV | Parse Notion's export structure | | Logseq | Markdown with `((block refs))` | Convert block refs to page links | | Plain markdown | Any .md directory | Import directory into gbrain directly | | CSV | Tabular data | Map columns to frontmatter fields | | JSON | Structured data | Map keys to page fields | | Roam | JSON export | Convert block structure to pages | ## Phases 1. **Assess the source.** What format? How many files? What structure? 2. **Plan the mapping.** How do source fields map to gbrain fields (type, title, tags, compiled_truth, timeline)? 3. **Test with a sample.** Import 5-10 files, verify by reading them back from gbrain and exporting. 4. **Bulk import.** Import the full directory into gbrain. 5. **Verify.** Check gbrain health and statistics, spot-check pages. 6. **Build links.** Extract cross-references from content and create typed links in gbrain. ## Obsidian Migration 1. Import the vault directory into gbrain (Obsidian vaults are markdown directories) 2. Wire the graph with native wikilink support (v0.12.1+): ```bash gbrain extract links --source db --dry-run | head -20 # preview gbrain extract links --source db # commit ``` `extract links` natively parses `[[relative/path]]` and `[[relative/path|Display Text]]` alongside standard `[text](page.md)` markdown syntax. Ancestor-search resolution handles wiki KBs where authors omit one or more leading `../` prefixes. The `.md` suffix is inferred automatically for wikilinks. Obsidian-specific: - Tags (`#tag`) become gbrain tags - Frontmatter properties map to gbrain frontmatter - Attachments (images, PDFs) are noted but handled separately via file storage ## Notion Migration 1. Export from Notion: Settings > Export > Markdown & CSV 2. Notion exports nested directories with UUIDs in filenames 3. Strip UUIDs from filenames for clean slugs 4. Map Notion's database properties to frontmatter 5. Import the cleaned directory into gbrain ## CSV Migration For tabular data (e.g., CRM exports, contact lists): 1. For each row in the CSV, create a page with column values as frontmatter 2. Use a designated column as the slug (e.g., name) 3. Use another column as compiled_truth (e.g., notes) 4. Store each page in gbrain ## Verification After any migration: 1. Check gbrain statistics to verify page count matches source 2. Check gbrain health for orphans and missing embeddings 3. Export pages from gbrain for round-trip verification 4. Spot-check 5-10 pages by reading them from gbrain 5. Test search: search gbrain for "someone you know is in the data" ## Anti-Patterns - **Bulk import without sample test.** Never import the full dataset before verifying with 5-10 files. The cost of cleaning up hundreds of bad pages is enormous. - **Destroying source data.** Migration is additive. Never modify, move, or delete the source files. - **Ignoring cross-references.** Wikilinks, block refs, and tags from the source system must be converted to gbrain equivalents. Dropping them loses the knowledge graph. - **Skipping verification.** A migration without post-import health check, page count comparison, and spot-check reads is incomplete. ## Output Format ``` MIGRATION REPORT -- [source] -> GBrain ======================================= Source: [format] ([file count] files, [size]) Mapping: [field mapping summary] Sample Test (N files): - Imported: N/N - Round-trip verified: N/N - Cross-refs converted: N Bulk Import: - Total imported: N - Skipped (duplicates/errors): N - Links created: N - Tags migrated: N Verification: - Page count match: [yes/no] - Health check: [pass/fail] - Search test: [query] -> [result count] hits ``` ## Tools Used - Store/update pages in gbrain (put_page) - Read pages from gbrain (get_page) - Link entities in gbrain (add_link) - Tag pages in gbrain (add_tag) - Get gbrain statistics (get_stats) - Check gbrain health (get_health)
From ltdrew/Agent-brain-2, MIT.
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install
ltdrew
No description from the publisher yet.
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Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Apr 18, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/ltdrew/Agent-brain-2
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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migrate skill. Agent Mart. https://agentmart.dev/skills/ltdrew-migrate (last updated 2026-10-24)