"name": "contact/enrich.requested", "data": { "name": "Person Name", "vault_path": "Contacts/Person Name.md", "depth": "full" } }

The synthesizer merges new data with existing content — it won't discard existing facts unless contradicted.

## VIP Contacts (ADR-0151)

Mark `vip: true` in frontmatter. VIPs get **deep enrichment + ongoing monitoring**.

### Deep Enrichment Playbook (one-time)

Every VIP gets the full treatment. This is what we did for Kent C. Dodds (Feb 26, 2026):

| Step | Source | What to Capture |
|---|---|---|
| 1. Web presence | Web search `{name} + {org}` | Bio, role, location, personal details |
| 2. Podcast/interviews | Web search `{name} podcast interview` | Appearance list, own podcasts, audiences |
| 3. Joel collaborations | Their website, appearances pages | Joint podcasts, co-organized events, shared projects |
| 4. Career timeline | Defuddle 2-3 key interview transcripts | Origin story, career arc, key decisions, values |
| 5. GitHub profile | GitHub API or web | Repos, followers, orgs, contribution patterns |
| 6. X/Twitter profile | X API v2 (use x-api skill) | Bio, followers, recent tweets, engagement |
| 7. Key relationships | Cross-reference transcripts + contacts | Who they work with, who they mention, who we know in common |
| 8. Content catalog | Website crawl (defuddle) | Courses, blog posts, open source projects |
| 9. Audience reach | Podcast counts, social followers | Conference circuit, community presence |

**Index to Typesense** after enrichment:
- Batch-import appearances/content to `discoveries` collection (NDJSON, `action=upsert`)
- Tag all docs with person's name slug (e.g. `kent-c-dodds`) for filtering
- Fields: `id`, `title`, `url`, `summary`, `tags[]`, `timestamp`
- Write a `Vault/Resources/{name}-media-appearances.md` reference doc linking back to contact

**Output sections** in the vault note:
- Background & Story (origin, career timeline)
- Teaching/Work Philosophy (or equivalent for non-educators)
- Key Relationships (cross-linked `[[wikilinks]]` to other contacts)
- Audience & Reach
- Content/Products
- Podcast/Collaboration History with Joel
- Recent Activity (timestamped)

### Ongoing Monitoring (Phase 2-4 of ADR-0151)

| Channel | Tool | Signal |
|---|---|---|
| Google Alerts | joelclawbot Google account | Name mentions in news, blogs, press |
| X/Twitter list | joelclaw X account | Tweets, engagement |
| GitHub activity | GitHub API (polling) | New repos, releases |
| Podcast RSS | Feed monitoring | New episodes |
| Website changes | Periodic defuddle + diff | Blog posts, launches, bio changes |

**High-signal** (immediate): course launches, role changes, mentions of Joel/egghead/Skill, fundraising.
**Low-signal** (daily/weekly digest): regular tweets, blog posts, OSS activity.

### Current VIPs
- Get notified to Joel via gateway after enrichment
- Are refreshed weekly via scheduled cron
- Have priority in channel intelligence pipeline (ADR-0131, ADR-0132)
- Get ongoing monitoring when ADR-0151 Phase 2+ is implemented

## Roam Research Enrichment

Joel's Roam archive (`~/Code/joelhooks/egghead-roam-research/`) contains the full egghead-era graph (2019-2024). Many contacts have extensive history there.

### Quick Search (Python regex)
```bash
cd ~/Code/joelhooks/egghead-roam-research
python3 -c "
import re
with open('egghead-2026-01-19-13-09-38.edn', 'r') as f:
    content = f.read()
pattern = r':block/string\s+\"([^\"]*?)\"'
matches = []
for m in re.findall(pattern, content):
    if '[[SEARCH_TAG]]' in m.lower():
        matches.append(m)
print(f'Found {len(matches)} blocks')
for m in matches[:30]:
    print(f'  - {m[:200]}')
"

People Taxonomy

People are tagged with relationship prefixes in Roam:

• [[collaborator/Name]] — Strategic partners (Ian Jones, Alex Hillman)
• [[client/Name]] — egghead instructors (Matt Pocock, Jacob Paris)
• [[staff/Name]] — egghead team (Will Johnson, Daniel Miller, Maggie Appleton)
• [[name]] (no prefix) — Informal references (Zac is [[zac]])

Page Title Search

python3 -c "
import re
with open('egghead-2026-01-19-13-09-38.edn', 'r') as f:
    content = f.read()
pattern = r':node/title\s+\"([^\"]*?SEARCH_TERM[^\"]*?)\"'
for m in re.findall(pattern, content):
    print(f'  page: {m}')
"

Adding to Contacts

When extracting person data from Roam, add roam_tag to frontmatter:

roam_tag: "[[collaborator/Ian Jones]]"

This enables future re-queries and cross-referencing.

Datalog Queries (advanced)

The EDN file is Datomic-style. Clojure scripts exist at scripts/ for structured analysis. See the roam-research skill for full Datalog patterns.

Resolving Unknown People

When you encounter a Slack user ID (<@U0XXXXXXX>):

# Lease token and look up profile
SLACK_USER=$(secrets lease slack_user_token --ttl 5m)
curl -s "https://slack.com/api/users.info?user=U0XXXXXXX" \
  -H "Authorization: Bearer $SLACK_USER" | jq '.user.real_name, .user.profile.email'
# Revoke only the exact lease ids acquired by this task; never all sessions’ leases.

Then fire enrichment with the resolved name and hints.

Inngest Function

• Function: contact-enrich (packages/system-bus/src/inngest/functions/contact-enrich.ts)
• Event: contact/enrich.requested
• ADR: ~/Vault/docs/decisions/0133-contact-enrichment-pipeline.md
• Concurrency: 3 max
• Sources: Slack, Slack Connect, Roam archive, GitHub/web, Granola meetings, Brain-backed recall, and other indexed sources

Privacy

• Contact files are in Vault (private, not in public repos)
• Slack data stays private — never surface in public content
• Email/phone are stored for Joel's reference only