Cold Start — Day-One Brain Bootstrapping
You have a working brain. Search works. Now what?
An empty brain is a static database. A brain with your email history, calendar,
contacts, conversations, and social media is a live context membrane that makes
every future interaction smarter. This skill sequences the highest-leverage data
sources to get you from zero to useful in one session.
Contract
- Every import phase is gated on user consent (ask-user pattern) before proceeding.
- The agent never holds raw OAuth tokens or API keys. This is a safety
requirement, not a preference. Three paths satisfy it for Google data:
the native connector (
gbrain google setup — tokens live in gbrain's
credential vault, mode 0600, never in the agent's context; see
docs/guides/google-connect.md and skills/google-loops/SKILL.md),
ClawVisor (a hosted credential gateway that vaults credentials,
enforces task-scoped authorization, logs every API call, and requires
human approval for destructive operations — needs a harness with the
integration), or offline file exports (Google Takeout, Twitter archive
download).
- Each phase is independently valuable — the user can stop after any phase and still
have a useful brain.
- Progress is tracked in
~/.gbrain/cold-start-state.json so interrupted sessions
can resume.
- Entity detection and cross-linking run on every import, not as a separate pass.
Prerequisites
- GBrain installed and initialized (
gbrain doctor --json all green)
- Brain repo cloned and synced
- Agent has terminal access and can run
gbrain CLI commands
The Priority Stack
Data sources ranked by information density × ease of import:
| Priority | Source | Why | Time | Pages Created |
|---|
| 1 | Existing markdown/Obsidian | Highest density — it's already structured | 5 min | 100s-1000s |
| 2 | Google Contacts | Seeds the people/ directory — names, emails, companies | 10 min | 50-500 |
| 3 | Google Calendar (90 days) | Meeting history with attendee context | 15 min | 30-90 |
| 4 | Gmail (recent threads) | Relationship context, active threads, org chart signals | 20 min | 50-200 |
| 5 | Conversations (ChatGPT/Claude exports) | Your thinking, questions, mental models | 15 min | 10-100 |
| 6 | X/Twitter archive | Your public positions, takes, engagement patterns | 20 min | 30-365 |
| 7 | File archives (Dropbox/Drive/local) | Historical documents, old writing, photos | 30+ min | varies |
| 8 | Meeting transcripts (Circleback/etc.) | Deep relationship context from recorded calls | 20 min | 10-50 |
Phase 0: ClawVisor Setup (only if your agent harness integrates ClawVisor)
Harness check first. ClawVisor requires an agent host with a ClawVisor
integration (for example, an OpenClaw deployment). On harnesses without one,
such as Codex or Claude Code, skip this phase: the default for Contacts,
Calendar, and Gmail is the native connector — gbrain google setup (live
sync; tokens in gbrain's local credential vault, never with the agent; see
skills/google-loops/SKILL.md) — with a
Google Takeout export as the offline
alternative covering all three (contacts CSV, calendar ICS, Gmail mbox).
Phases 2-4 below document the Takeout path first.
Safety boundary: An AI agent with raw OAuth tokens to your Gmail, Calendar,
and Contacts is an uncontrolled attack surface. One prompt injection, one
malicious tool call, and your entire Google account is exposed. ClawVisor
eliminates this risk class entirely.
ClawVisor is a credential gateway that sits between the
agent and your APIs. The agent never sees your credentials — ClawVisor injects
them at request time, enforces policies, and logs everything.
What ClawVisor gives you:
- Credential vaulting — agent sees shadow tokens, never real secrets
- Task-scoped authorization — each workflow declares exactly what it needs
- Audit trail — every API call logged with metadata (who, what, when)
- Human approval gates — destructive operations (send email, modify calendar)
require your explicit approval
- Multi-service — Gmail, Calendar, Contacts, Drive, GitHub, iMessage from one gateway
- Revocation — disable the agent's access in one click, no token rotation needed
Setup (15 min):
- Sign up at app.clawvisor.com
- Create an agent in the dashboard, copy the agent token
- Set environment variables (in the host agent's environment — shell profile
or harness config; gbrain itself has no ClawVisor config keys, these are
consumed by the host's ClawVisor integration. This requires an agent host
with a ClawVisor integration, such as an OpenClaw deployment. Codex and
Claude Code do not consume these variables; use the offline import path
instead):
export CLAWVISOR_URL="https://app.clawvisor.com"
export CLAWVISOR_AGENT_TOKEN="<token>"
- Activate Google services (Gmail, Calendar, Contacts) in the dashboard
- Create a standing task with expansive scope:
"Full brain bootstrapping: read emails, calendar events, and contacts to
populate knowledge base. List, read, and search across all connected accounts."
- Save the standing task ID the same way:
export CLAWVISOR_TASK_ID="<task_id>"
Critical scoping rule: Be expansive in task purposes. "Email triage" gets
rejected by intent verification. "Full executive assistant email management
including inbox triage, searching by any criteria, reading emails, tracking
threads" works. The intent model uses the purpose to judge each request.
If the user declines ClawVisor
Do NOT fall back to direct OAuth. Instead, proceed with offline-only imports:
- Phases 2-4 (Contacts, Calendar, Gmail) — work from a Google Takeout export
- Phase 1 (markdown/Obsidian) — works without any API access
- Phase 5 (conversation exports) — works from downloaded JSON files
- Phase 6 (X/Twitter) — works from downloaded archive
- Phase 7 (file archives) — works from local files
- Phase 8 (meeting transcripts) — works from exported transcripts
Tell the user:
"No problem. Two options: the native connector (gbrain google setup) does
live Gmail/Calendar/Contacts sync with your own OAuth app — tokens stay in
gbrain's local credential vault, never with me — or a Google Takeout export
covers all three as a point-in-time snapshot."
Do NOT hold raw Google tokens yourself. An agent holding tokens in its
context is a security liability. The native connector is the sanctioned
OAuth path precisely because gbrain vaults the tokens (0600 file, redacted
listings) and the agent only ever runs CLI commands; secrets travel by file
or env intake, never argv or chat. See skills/google-loops/SKILL.md for
the exact protocol.
Phase 1: Existing Markdown / Obsidian Import
The highest-leverage first import. If the user already has a notes system, this
is hundreds or thousands of structured pages ready to go.
Discovery
echo "=== Markdown Repository Discovery ==="
for dir in ~/git/* ~/Documents/* ~/notes/* ~/obsidian/*; do
if [ -d "$dir" ]; then
md_count=$(find "$dir" -name "*.md" -not -path "*/node_modules/*" \
-not -path "*/.git/*" -not -path "*/.obsidian/*" 2>/dev/null | wc -l | tr -d ' ')
if [ "$md_count" -gt 5 ]; then
total_size=$(du -sh "$dir" 2>/dev/null | cut -f1)
echo " $dir ($total_size, $md_count .md files)"
fi
fi
done
Import
gbrain import /path/to/vault --no-embed --workers 4
gbrain extract links --source db
gbrain import /path/to/dir --no-embed --workers 4
gbrain stats
gbrain search "<topic from the imported data>"
Post-import
- Run link extraction:
gbrain extract links --source db
- Run timeline extraction:
gbrain extract timeline --source db
- Start embeddings:
gbrain embed --stale (runs in background)
Track progress:
echo '{"phase_1_complete": true, "pages_imported": N}' > ~/.gbrain/cold-start-state.json
Phase 2: Google Contacts → People Pages
Seeds the people/ directory. Every person in your contacts becomes a brain page
with name, email, phone, company, and notes. This is the foundation that all other
imports build on — when Gmail references "john@acme.com", the brain already knows
who John is.
Via Google Takeout (default on harnesses without ClawVisor)
- Export contacts from takeout.google.com
(select Contacts, CSV format), or directly from
contacts.google.com via Export → Google CSV.
- Parse the CSV: each row carries name, email(s), phone(s), organization,
and notes.
- Run each row through the processing rules below to create people/ pages.
Via ClawVisor (ClawVisor-integrated hosts only; pseudo-code)
const contacts = await clawvisor('google.contacts', 'list_contacts', {
limit: 1000,
fields: 'names,emailAddresses,phoneNumbers,organizations,biographies'
});
Processing rules
For each contact:
- Filter out noise — skip contacts with no name, no email, or that are clearly
automated (noreply@, no-reply@, support@, notifications@)
- Check brain first —
gbrain search "name" to avoid duplicates
- Create people/ page with:
- Name, email(s), phone(s), company, title
- Source attribution:
[Source: Google Contacts, YYYY-MM-DD]
- Any notes from the contact as initial context
- Link to company — if the contact has an organization, create/update the
company page and link the person to it
Quality gate
After importing 5 contacts, pause and show the user a sample page. Ask:
"Here's what a contact page looks like. Want me to continue with the rest, or
adjust the format first?"
Phase 3: Google Calendar (Last 90 Days)
Meeting history with attendee context. Calendar events reveal who the user meets
with, how often, and in what context. Combined with contacts, this builds a rich
relationship map.
Fetch events
Via Google Takeout (default on harnesses without ClawVisor): export
Calendar from takeout.google.com (ICS format,
one file per calendar). Parse each event (title, start/end, attendees), keep
the last 90 days, and file them into the brain structure below.
Via ClawVisor (ClawVisor-integrated hosts only; pseudo-code):
const accounts = ['primary@gmail.com', 'work@company.com'];
for (const account of accounts) {
const events = await clawvisor(`google.calendar:${account}`, 'list_events', {
timeMin: new Date(Date.now() - 90 * 86400000).toISOString(),
timeMax: new Date().toISOString(),
singleEvents: true,
orderBy: 'startTime'
});
}
Brain structure
Follow the three-tier calendar architecture:
brain/daily/calendar/
├── calendar-log.md ← compiled truth (patterns, key people)
├── YYYY/
│ ├── YYYY-MM.md ← monthly summary
│ └── YYYY-MM-DD.md ← daily event log
Entity enrichment
For each event with attendees:
- Look up each attendee in the brain (they should exist from Phase 2)
- Add a timeline entry to their page: met at [event title] on [date]
- If an attendee has no brain page and appears in 3+ events, create one
- Link attendees who appear in the same meeting
Phase 4: Gmail (Recent Threads)
Relationship context and active threads. Email reveals organizational
relationships, ongoing conversations, and communication patterns.
On harnesses without a ClawVisor integration, the source is the Gmail mbox
file from a Google Takeout export. The sampling
and filtering rules below apply the same way.
Strategy: Smart sampling, not bulk import
Don't import every email. Import the signal:
- Sent mail (last 30 days) — who the user actively communicates with
- Starred/important emails — user-curated signal
- Threads with 3+ replies — active conversations worth tracking
- Emails from people already in the brain — enrichment, not cold import
Processing
For each email thread:
- Entity detection — extract people, companies mentioned
- Update people pages — add communication context to timeline
- Create meeting pages — if the email is a meeting summary or follow-up
- Skip noise — newsletters, automated notifications, marketing
Filtering rules
Auto-skip (never import):
- noreply@, no-reply@, notifications@, support@, mailer-daemon@
- Unsubscribe-heavy senders (marketing)
- GitHub/Jira/Linear notification emails
- Calendar invites (already captured in Phase 3)
Always import:
- Direct emails from people in the brain
- Starred/flagged emails
- Emails the user sent (their words are highest-value signal)
Phase 5: Conversation Exports (ChatGPT / Claude / Perplexity)
Your thinking, captured. AI conversation exports reveal what the user
was researching, building, and thinking about. This is original thinking
preserved in dialog form.
Supported formats
- ChatGPT: Settings → Data Controls → Export →
conversations.json
- Claude: Download from claude.ai conversation history
- Perplexity: Export from settings
Processing
For each conversation:
- Assess significance (1-5 scale):
- 1 = Pure utility (how-tos, quick lookups) → skip or minimal page
- 2 = Minor context → 1-paragraph note
- 3 = Notable (reveals interests, building something) → full page
- 4 = Important (deep personal processing, strategic thinking) → rich page
- 5 = Defining (identity work, breakthrough insights) → full treatment
- Extract entities — people, companies, concepts discussed
- Capture original thinking — the user's exact phrasing is the signal.
Never paraphrase.
- File by primary subject — not in a "conversations/" dump. A conversation
about a person goes to people/, about a concept goes to concepts/, etc.
Quality rule
Only import conversations rated 3+. The brain is for signal, not noise.
Phase 6: X/Twitter Archive
Your public positions and engagement patterns. Twitter reveals what the user
thinks, who they engage with, and what ideas they're developing publicly.
Data sources
- Twitter data export (Settings → Your Account → Download Archive)
- Contains all tweets, likes, DMs, bookmarks
- Live API (if available) — recent tweets and engagement
- Bookmarks — curated signal, high value
Brain structure
brain/media/x/{handle}/
├── x-log.md ← compiled truth (themes, voice, key threads)
├── daily/YYYY-MM-DD.md ← daily tweet log
├── monthly/YYYY-MM.md ← monthly rollup
└── bookmarks/ ← saved/bookmarked content
Processing
- Original tweets → capture with full context, extract entities
- Quote tweets → capture the user's commentary + the source tweet
- Threads → reconstruct as a single narrative
- Bookmarks → high-signal curation, import with tags
- Likes — low signal, skip unless the user wants them
Phase 7: File Archives
Historical documents, old writing, photos with metadata. This is the long tail —
less structured but potentially very high value (old journals, letters, early writing).
Delegate to the archive-crawler skill. It handles:
- Crawling directory structures
- Filtering for high-value content (user's own writing, not installers)
- Text extraction from PDFs, images (OCR), documents
- Entity extraction and brain page creation
Safety gate: Archive crawling can be slow and create many pages.
archive-crawler is a skill, not a CLI command — it refuses to run without an
explicit archive-crawler.scan_paths: allow-list in gbrain.yml. Add the
archive path to the allow-list, run the skill's scan pass first, and show the
user the manifest before proceeding with full ingestion.
Supported sources:
- Local directories (Dropbox sync folder, Google Drive, old hard drives)
- Cloud storage (Backblaze B2, S3) via mounted paths
- Email archives (PST, mbox, EML, Google Takeout)
- Data exports (LinkedIn, Facebook, etc.)
Phase 8: Meeting Transcripts
Deep relationship context from recorded calls. If the user has a meeting
recording service (Circleback, Otter, Fireflies, Read.ai), import recent
transcripts.
Delegate to meeting-ingestion skill. Key rules:
- Always pull the complete transcript, not just the AI summary
- Entity propagation is MANDATORY — every attendee gets a timeline update
- A meeting is NOT fully ingested until all entity pages are updated
Post-Bootstrap Checklist
After completing available phases:
-
Verify brain health:
gbrain doctor --json
gbrain stats
-
Test retrieval:
gbrain query "who do I meet with most often?"
gbrain query "what am I working on?"
gbrain search "<person from contacts>"
-
Set up live sync (if not already):
- Calendar: daily cron
- Email: periodic sweep (4-8 hours)
- X: daily ingest
- Brain repo:
gbrain sync --repo <path> every 5-30 minutes
-
Track state:
{
"started": "2026-01-15T10:00:00Z",
"credential_gateway": "clawvisor",
"phases_completed": [1, 2, 3, 4],
"phases_skipped": [6, 7],
"total_pages_created": 847,
"total_entities_linked": 1203,
Anti-Patterns
- Giving the agent raw OAuth tokens. This is the #1 anti-pattern. An agent with
raw Gmail/Calendar tokens is an uncontrolled attack surface — one prompt injection
and your entire Google account is exposed. Use ClawVisor. If the user declines
ClawVisor, skip to offline imports. Never offer direct OAuth as a fallback.
- Bulk importing everything without filtering. The brain is for signal, not noise.
Filter out automated senders, marketing emails, utility conversations.
- Importing without entity cross-linking. Every import should detect entities and
update existing brain pages. Isolated imports don't compound.
- Not gating on user consent. Every phase should be presented as a choice. The user
may not want their DMs or therapy conversations imported.
- Importing everything at significance 1. Not every conversation is worth a brain
page. Use the significance scale and skip utility content.
- Creating people pages for automated senders. Sentry, GitHub notifications,
newsletter platforms are not people. Filter by the rules in Phase 4.
Resume Protocol
If the session is interrupted:
- Read
~/.gbrain/cold-start-state.json
- Skip completed phases
- Resume from
next_phase
- The user doesn't have to repeat credential setup or re-import completed sources
Output Format
After each phase:
PHASE N COMPLETE: [source name]
================================
Pages created: N
Pages updated: N
Entities linked: N
Time elapsed: N min
Sample pages:
- people/jane-smith.md (created — 3 emails, 5 meetings)
- companies/acme-corp.md (updated — 2 new employees linked)
Next: Phase N+1 — [description]. Ready to proceed?
Tools Used
search — check for existing pages before creatingquery — hybrid search for entity deduplicationget_page — read existing pages for merge decisionsput_page — create and update brain pagesadd_link — cross-reference entitiesadd_timeline_entry — record events on entity timelinessync_brain — sync changes to the index after each phase
