/pipeline — work the leads (today's actions)
🧒 When reporting to a non-technical operator: end with a child-simple "In plain words" recap in their language. NEVER inside lead messages.
📖 Operates under the bible skill — outreach codex _Bible-Outreach-MOC. Outbound = send-direct (the operator 2026-06-16 — they edit the sent message after); NO mass auto-blast (pace + personalize per lead). Money / commitments / credentials → escalate.
🖥️ Dashboard first (the operator works visually)
python "$IMPORTS_ROOT/build_pipeline_dashboard.py" → open $OBSIDIAN_VAULT/_Dashboards/Pipeline-Dashboard.html: a kanban by stage (🔥 replied → ⏰ nudge → ⏳ booked → 👀 waiting → ✅ done) + ready drafts (click = copy). View only, it sends nothing. The text walkthrough below is for the actions themselves (send-direct, the operator edits after the fact).
Step 1 — Load live pipeline state (deterministic, ~free)
Read $IMPORTS_ROOT/tg_followups.json (the watcher's live state). Each pending[] lead: lead, chat_id, username, pitch_sent, calendly_sent, replied, booked, booking_confirmed, + a check instruction. Plus calendly_sent_at (for the 24h nudge) and booking_nudge_rule.
Deeper history per lead: 04-Projects\crypto\Platinum-CRM\_Platinum-CRM-MOC.md + its lead cards, or /ask --leads "<name>".
Step 2 — Classify each lead → TODAY's action (priority order)
- 🔥 Replied, Calendly not sent (
replied set, calendly_sent:false) → draft calendly_text to that chat. Warm NOW = top priority.
- ⏰ Calendly sent ≥24h, not booked (
calendly_sent:true, no booking_confirmed, calendly_sent_at >24h ago) → draft booking_nudge_text (leads forget to book — standing rule).
- 👀 Awaiting reply (
pitch_sent:true, no replied) → run the lead's check: read recent messages of chat_id (Telegram MCP; see telegram-howto) for a NEW inbound (sender ≠ Tony) after our pitch. If replied → it becomes case 1.
- ❄️ Going cold (pitched long ago, no reply, no nudge) → propose ONE soft follow-up, or mark to drop.
- ✅ Booked/confirmed → close out; suggest removing from
pending. Never re-pitch.
Step 3 — Output the worklist, then act on the operator's go
- Show a ranked table: lead · state · proposed action · exact draft text.
- Send each directly (the operator edits the sent message if something's off); NO mass auto-blast — pace + personalize per lead.
- After sending, UPDATE
tg_followups.json (calendly_sent, booking_confirmed, booking_nudge_sent…) so state stays true.
- Refresh the lead's CRM card (telegram-lead-outreach capture step).
- End with 🧒 recap.
Guardrails
- Voice = the operator's words verbatim (their rule); concise, no filler.
- Money / commitments / credentials → escalate, never autonomous.
- If
tg_followups.json is empty/stale → say so; offer to rebuild from recent Telegram via telegram-lead-outreach ("find + capture").
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Like this skill? It is part of second-brain-starter-kit: the second brain we built for ourselves and run every day at Palo Alto AI Research Lab. Install the whole set with npx skills add tonydzi/second-brain-starter-kit. Everything is open source and free, so take what you need.
Flagships worth a look on their own: secondop-panel (a second opinion from a panel of external models), claude-memory-tidy (stop your agent's memory from rotting), telegram-mcp-kit (your own Telegram over MCP in about 15 minutes).
Author: Anton Dziatkovskii, Palo Alto AI Research Lab. Telegram @tonydzi - WhatsApp +1 341 222 9178 - X @Tony_Stef_
Engineers: want to test-drive this setup? Message me. I hand out free starter seeds to engineers who test and report back, and custom skill requests are welcome.