O.C. Manjos Lead Qualifier

SkillDatabases & data

Qualifies inbound sales enquiries from a Supabase-backed WhatsApp sales AI and places outbound follow-up calls via CALL-E for high-value, recently-active leads.

Available today. Use it from your connected AI after setup.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the O.C. Manjos Lead Qualifier skill

What this skill tells your AI

The instructions your AI receives, as published by calle-ai/awesome-phone-call-agents in skills/ocmanjos-lead-qualifier/SKILL.md and read by ahel’s review.

Scores inbound product enquiries (captured via a WhatsApp sales AI into Supabase) against category, price, and recency rules, then places a CALL-E outbound call to qualifying leads to confirm interest and capture delivery or pickup preference.

Use it for

  • Following up on high-value product enquiries that went unanswered on WhatsApp within 72 hours
  • Confirming customer interest and delivery preference via voice instead of relying on repeat text follow-ups
  • Demonstrating a real small-business use case for CALL-E: filtering noisy, free-text enquiry data down to genuinely qualifying leads before spending a call

Do not use it to

  • Call numbers not sourced from an explicit customer enquiry
  • Call leads marked as already purchased, a known competitor, or opted out
  • Guess phone numbers, prices, or product categories - the skill only prices and calls what matches configured rules and real price-sheet data

Setup

  1. A Supabase table with enquiry records (product_asked, created_at, whatsapp_responded, known_competitor, already_purchased, opted_out)
  2. A product price sheet (.xlsx) with description, unit price, and sell price columns
  3. .env with SUPABASE_URL and SUPABASE_ANON_KEY (never commit this file)
  4. CALL-E CLI authenticated (calle auth login)

How it works

  1. Pull recent enquiries from Supabase
  2. Extract a product keyword and variant (e.g. size/phase) from free-text product_asked
  3. Look up the real sell price from the price sheet, matched by token, not exact phrase
  4. Score against category/price/recency/disqualifier rules
    1. For qualifying leads, the operator manually runs CALL-E's plan_call via the CLI, reviews the confirm_summary, then runs run_call. This script identifies who to call; it does not itself invoke CALL-E.

Qualification rule (example, tune to your own product line)

IF (category = "Distribution Board" AND value >= 35000) OR (category = "Box/Conduit" AND value >= 2500) OR (category = "Solar/Flood Light" AND value >= 34000) AND enquiry_age <= 72h AND no_whatsapp_response = true AND NOT (known_competitor OR already_purchased OR opted_out) THEN CALL

Side effects

This skill places real outbound phone calls when a lead qualifies. Each call consumes CALL-E call credits. Always review plan_call output (ready_to_run, confirm_summary) before calling run_call - this repository's rules prohibit placing a setup-time test call without the user explicitly asking for one.

Example (masked)

Phone: +15550101234 (masked example - never a real customer number in samples) Product: 3-phase distribution board (D6) Price: 42,500 NGN Result: customer confirmed interest, requested delivery, did not provide delivery details before call ended

Known limitations

  • Keyword/variant extraction currently only handles size and phase patterns for the Distribution Board category; other multi-variant product lines need similar extraction logic added
  • Phone numbers must currently be sourced manually until a WhatsApp Business API integration writes them into Supabase directly
  • Call-outcome confidence scoring can register high confidence on an abrupt or ambiguous call ending; treat completion_confidence as a signal, not a guarantee, and review transcripts for anything time-sensitive

Signals

GitHub stars
104
Forks
527
Last commit
Sep 2026
Advanced
Item type
skill
Key
ocmanjos-lead-qualifier
Source
github.com/calle-ai/awesome-phone-call-agents