evernote-migration-deep-dive
Guidance on bulk Evernote data exports, imports, and format conversion.
Install
mkdir -p .claude/skills/evernote-migration-deep-dive && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/4098" && unzip -o skill.zip -d .claude/skills/evernote-migration-deep-dive && rm skill.zipInstalls to .claude/skills/evernote-migration-deep-dive
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Deep dive into Evernote data migration strategies.Key capabilities
- →Assess migration scope and estimate API quota consumption
- →Export Evernote notes to ENEX, JSON, or Markdown formats
- →Convert source data to ENML for Evernote import
- →Implement migration runners with checkpointing and resume
- →Verify data integrity using note counts and content hashes
How it works
The tool assesses migration volume, converts data formats, and uses a migration runner to bulk-create notes while handling rate limits and verifying integrity.
Inputs & outputs
When to use evernote-migration-deep-dive
- →Plan large-scale Evernote migrations
- →Convert formats during transfer
- →Verify data integrity post-migration
- →Manage API rate limits during bulk import
About this skill
Evernote Migration Deep Dive
Current State
!npm list 2>/dev/null | head -5
Overview
Comprehensive guide for migrating data to and from Evernote, including ENEX export/import, bulk API operations, format conversions (ENML to Markdown, HTML to ENML), and data integrity verification.
Prerequisites
- Understanding of Evernote data model (Notes, Notebooks, Tags, Resources)
- Source/target system access credentials
- Sufficient API quota for migration volume
- Backup strategy in place before starting
Instructions
Step 1: Migration Planning
Assess the migration scope: count notes, notebooks, tags, and total resource size. Estimate API call count and quota consumption. Plan for rate limits (add delays between operations).
async function assessMigration(noteStore) {
const notebooks = await noteStore.listNotebooks();
const tags = await noteStore.listTags();
let totalNotes = 0;
for (const nb of notebooks) {
const filter = new Evernote.NoteStore.NoteFilter({ notebookGuid: nb.guid });
const spec = new Evernote.NoteStore.NotesMetadataResultSpec({});
const result = await noteStore.findNotesMetadata(filter, 0, 1, spec);
totalNotes += result.totalNotes;
}
return {
notebooks: notebooks.length,
tags: tags.length,
totalNotes,
estimatedApiCalls: totalNotes * 2 + notebooks.length + tags.length,
estimatedTimeMinutes: Math.ceil((totalNotes * 2 * 200) / 60000) // 200ms per call
};
}
Step 2: Export from Evernote
Export notes in three formats: ENEX (Evernote's XML format, preserves everything including resources), JSON (structured data for programmatic use), or Markdown (human-readable, loses some formatting).
async function exportToMarkdown(noteStore, noteGuid) {
const note = await noteStore.getNote(noteGuid, true, true, false, false);
const text = enmlToMarkdown(note.content);
return {
title: note.title,
content: text,
tags: note.tagNames || [],
created: new Date(note.created).toISOString(),
resources: (note.resources || []).map(r => ({
filename: r.attributes.fileName,
mime: r.mime,
size: r.data.size
}))
};
}
Step 3: Import to Evernote
Convert source data to ENML format, create notebooks to match source structure, and bulk-create notes with rate limit handling. Verify each import by comparing note counts and content hashes.
Step 4: Migration Runner
Build a migration runner with progress tracking, checkpointing (resume from failure), and verification. Log every operation for audit trail.
For the full migration planner, ENEX parser, format converters, migration runner, and verification tools, see Implementation Guide.
Output
- Migration assessment tool (note count, estimated time, quota needs)
- ENEX, JSON, and Markdown exporters
- ENML importer with format conversion
- Migration runner with progress tracking and checkpoint/resume
- Post-migration verification (count comparison, content hash check)
Error Handling
| Error | Cause | Solution |
|---|---|---|
QUOTA_REACHED | Upload quota exceeded during import | Wait for quota reset or upgrade account tier |
RATE_LIMIT_REACHED | Too many API calls during bulk migration | Increase delay between operations, use checkpointing |
BAD_DATA_FORMAT | Source content not valid ENML | Validate and sanitize content before import |
| Lost resources | Attachments not migrated | Verify resource hashes match after migration |
Resources
- Evernote Export Format (ENEX)
- ENML Reference
- API Reference
- Synchronization
Examples
Export all notes to Markdown: Iterate through all notebooks, export each note as a Markdown file with frontmatter (title, tags, date), save resources to assets/ directory, preserving notebook-as-folder structure.
Import from Notion: Parse Notion export (Markdown + CSV), convert to ENML, create matching notebooks, and bulk-import with checkpoint/resume for large exports (10,000+ pages).
When not to use it
- →When source content is not valid ENML
- →When API upload quota is exceeded
Prerequisites
Limitations
- →API rate limits require added delays
- →Markdown export loses some original formatting
How it compares
Unlike manual exports, this approach provides automated checkpointing, resume capabilities, and programmatic verification of content hashes.
Compared to similar skills
evernote-migration-deep-dive side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| evernote-migration-deep-dive (this skill) | 1 | 25d | Review | Intermediate |
| streamlit | 86 | 9mo | No flags | Intermediate |
| jupyter-notebook | 30 | 6mo | Review | Intermediate |
| backtesting-frameworks | 17 | 2mo | No flags | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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