
Migrate
- 33 installs
- 17.2k repo stars
- Updated August 1, 2026
- danielmiessler/personal_ai_infrastructure
Imports external content from files, Obsidian, Notion, CLAUDE.md, or Cursor rules, classifies each chunk, and routes it into PAI destinations with an approval loop.
About
Intakes existing content from external sources, classifies each chunk against the PAI destination taxonomy, and commits approved chunks with provenance. A developer uses it to bulk-import notes, rules, and exports into a PAI structure with confidence-gated approval.
- Confidence gating: >=70% auto-approve, 40-70% confirm, <40% walk-through
- Provenance HTML comment on every commit and substring dedup
Migrate by the numbers
- 33 all-time installs (skills.sh)
- Ranked #1,197 of 2,715 Automation & Workflows skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 33 |
|---|---|
| repo stars | ★ 17.2k |
| Last updated | August 1, 2026 |
| Repository | danielmiessler/personal_ai_infrastructure ↗ |
What it does
Imports external content from files, Obsidian, Notion, CLAUDE.md, or Cursor rules, classifies each chunk, and routes it into PAI destinations with an approval loop.
Files
Migrate — external-content intake and classification
🚨 MANDATORY: Voice Notification
curl -s -X POST http://localhost:31337/notify \
-H "Content-Type: application/json" \
-d '{"message": "Starting the migration. Scanning source and classifying chunks."}' \
> /dev/null 2>&1 &What this skill does
Migrates content into the PAI structure from external sources. Unlike /interview (which asks the user questions to fill gaps), /migrate already has the content — it just needs to classify each chunk and route it to the right PAI destination.
Sources supported in V1
- Files:
.md,.markdown,.txt(single file or directory recursion) - Stdin: piped content or pasted directly
- Other PAI installs: point at their
USER/TELOS/orMEMORY/KNOWLEDGE/directories - Agent-harness rule files:
CLAUDE.md,.cursorrules, OpenAI Custom Instructions export - Exports: Obsidian vaults (markdown), Notion exports (markdown), Apple Notes exports (.txt), raw journal dumps
What it classifies chunks into
| Category | Destinations |
|---|---|
| Foundational TELOS | MISSION, GOALS, PROBLEMS, STRATEGIES, CHALLENGES, BELIEFS, WISDOM, MODELS, FRAMES, NARRATIVES, SPARKS |
| IDEAL_STATE dimensions | HEALTH, MONEY, FREEDOM, RELATIONSHIPS, CREATIVE, RHYTHMS |
| Preference files | BOOKS, AUTHORS, MOVIES, BANDS, RESTAURANTS, FOOD_PREFERENCES, LEARNING, MEETUPS, CIVIC |
| Identity | USER/PRINCIPAL_IDENTITY.md |
| Knowledge | MEMORY/KNOWLEDGE/{Ideas,People,Companies,Research} |
| AI collaboration rules | memory/feedback_*.md (for "always do X", "never Y" patterns) |
| Unclear | Flagged for the user's manual routing |
Workflow
Phase 1 — Identify the source
Ask the user what he wants to migrate:
- "Paste the content here and I'll work from stdin"
- "Point me at a file path"
- "Point me at a directory and I'll scan everything inside"
- "I have a Cursor rules file at ~/Projects/X/.cursorrules"
- "My old PAI install has TELOS at ~/old-claude/TELOS/"
Collect the source path. If content is pasted, write it to a temp file first.
Phase 2 — Scan
Run the scanner:
bun ~/.claude/PAI/TOOLS/MigrateScan.ts --source <path>
# or
echo "$CONTENT" | bun ~/.claude/PAI/TOOLS/MigrateScan.ts --stdinScanner output includes:
- Total chunks found
- Proposed routing table (how many chunks per target)
- Average classification confidence
- Count of UNCLEAR chunks
- Count of low-confidence (<40%) chunks
Phase 3 — Present routing summary
Show the user the routing proposal in a scannable format:
Found 47 chunks from 3 files. Proposed routing:
📂 TELOS/GOALS.md 12 chunks (78% avg confidence)
📂 TELOS/WISDOM.md 8 chunks (65% avg confidence)
📂 TELOS/BELIEFS.md 6 chunks (71% avg confidence)
📂 MEMORY/KNOWLEDGE/Ideas 15 chunks (52% avg confidence)
🧠 memory/feedback 4 chunks (85% avg confidence)
❓ UNCLEAR 2 chunks (needs your call)
Options:
- Approve everything trusted (confidence ≥60%)?
- Walk through the low-confidence and UNCLEAR chunks one by one?
- Review specific categories?
- Review everything?Phase 4 — Approval loop
Based on the user's preference:
Fast path (he says "approve all trusted"):
bun ~/.claude/PAI/TOOLS/MigrateApprove.ts --approve-allCommits everything non-UNCLEAR. Then walk through UNCLEAR chunks conversationally.
Category path (he says "approve goals and wisdom, skip knowledge"):
bun ~/.claude/PAI/TOOLS/MigrateApprove.ts --approve-target TELOS/GOALS.md
bun ~/.claude/PAI/TOOLS/MigrateApprove.ts --approve-target TELOS/WISDOM.mdWalk-through path (he wants careful review):
bun ~/.claude/PAI/TOOLS/MigrateApprove.ts --reviewShow each pending chunk. For each:
- Show preview + proposed target + confidence + alternatives
- Ask: approve / modify target / reject
- Commit decision
Phase 5 — Handle UNCLEAR chunks
UNCLEAR chunks are ones where no classification rule matched strongly. For each:
- Display full content (not just preview)
- Ask the user: "This one's unclear — what is it? Could be X, Y, Z, or maybe Knowledge/Ideas as a catch-all?"
- the user chooses → commit via
--modify <id> --target <chosen>
Phase 6 — Completion summary
After approval pass:
- Report total chunks committed, per-target count
- Flag any remaining UNCLEAR
- Recommend next step: run
/interviewto interview around anything the migration left sparse
Rules
- Every commit carries provenance. The committed content includes an HTML comment noting source file + section + timestamp. Nothing gets dropped into TELOS without attribution.
- Never bulk-approve UNCLEAR. Those require the user's explicit routing.
- Confidence thresholds: ≥70% = trusted (auto-approve eligible). 40-70% = medium (show for confirmation). <40% = low (walk-through required).
- Ask before touching identity. PRINCIPAL_IDENTITY.md commits always prompt — that file is load-bearing.
- Don't duplicate. If the same content already exists in the target (substring match), flag it and ask before appending.
- Respect private paths. Never migrate content into IDEAL_STATE/ without the user's per-dimension call (Decision #3: IDEAL_STATE is fully private and curated).
- Feedback memories get new files. Each
memory/feedbackchunk becomes its ownfeedback_migrated_<slug>_<id>.mdfile — not appended to an existing memory. - Knowledge gets new files too. Each
MEMORY/KNOWLEDGE/*chunk becomes a new typed note with source metadata.
Examples
User: /migrate ~/old-claude/TELOS/
the DA scans the old TELOS directory, classifies every chunk, presents the routing summary, offers fast-path vs. walk-through approval.
User: /migrate (then pastes CLAUDE.md content)
the DA reads from stdin, classifies the rules as memory/feedback (most) plus maybe PRINCIPAL_IDENTITY (if identity lines are mixed in), walks through approval.
User: "migrate my Cursor rules at ~/.cursor/rules"
the DA scans the rules dir, surfaces likely-feedback classifications, walks through with extra care (Cursor rules often have tool-specific stuff that doesn't translate to PAI).
User: "import the stuff I dumped in /tmp/journal.md"
the DA scans the journal, expects a lot of UNCLEAR + WISDOM, walks through each section.
Related
/interview— fills gaps by asking questions (not by intaking existing content)/TelosUpdate workflow — edit a single TELOS file directly/Knowledge— manage the Knowledge Archive/_PROFILE— manage PRINCIPAL_IDENTITY
Troubleshooting
- Low average confidence (<40%): the source is probably genre-mismatched (e.g., code comments, logs, raw data). Consider pre-filtering to remove non-prose chunks before scanning.
- Everything goes to UNCLEAR: the source probably has no recognizable PAI-taxonomy patterns. Either add the content manually via
/Telosor write it as general Knowledge notes. - Duplicate content warnings: the scanner doesn't dedupe against existing files yet. Run
--dry-runfirst to preview before committing.