whatsapp-lead-qualifier

whatsapp-lead-qualifier is a skill for Claude Code, Codex from InitechSoftware/openclaw-whatsapp-skills. It costs 96 tokens per session (2,473 once invoked), scanned A, original, MIT.

A multi-step WhatsApp conversation workflow that asks a fixed set of lead-qualification questions. It stores answers as chat notes and uses chat labels to track progress and the final qualified or disqualified result.

In plain words
What is it for?
Ask leads about their needs, team size, and timeline; record their answers; apply a qualification rule; and label the chat.
Why use it?
It removes the need for a separate database to remember where each conversation is and what the person answered. It also stops replying when the qualification sequence ends.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Ask leads about their needs, team size, and timeline; record their answers; apply a qualification rule; and label the chat.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/initechsoftware/openclaw-whatsapp-skills/whatsapp-lead-qualifier
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add InitechSoftware/openclaw-whatsapp-skills --skill whatsapp-lead-qualifier
Clone the repo
git clone --depth 1 https://github.com/InitechSoftware/openclaw-whatsapp-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for whatsapp-lead-qualifier

README.md
[![agentmods](https://agentmods.dev/badge/skills/initechsoftware/openclaw-whatsapp-skills/whatsapp-lead-qualifier/github.svg)](https://agentmods.dev/skills/initechsoftware/openclaw-whatsapp-skills/whatsapp-lead-qualifier)
Your own site
<a href="https://agentmods.dev/skills/initechsoftware/openclaw-whatsapp-skills/whatsapp-lead-qualifier"><img src="https://agentmods.dev/badge/skills/initechsoftware/openclaw-whatsapp-skills/whatsapp-lead-qualifier/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for whatsapp-lead-qualifier

Your own site · 80×15
<a href="https://agentmods.dev/skills/initechsoftware/openclaw-whatsapp-skills/whatsapp-lead-qualifier"><img src="https://agentmods.dev/badge/skills/initechsoftware/openclaw-whatsapp-skills/whatsapp-lead-qualifier.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 96 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,473 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00096 $0.02473
Opus 5 $0.00048 $0.01236
Sonnet 5 $0.00019 $0.00495
Haiku 4.5 $0.00010 $0.00247

Measured 11d ago against content hash 19e4226a546b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

whatsapp-lead-qualifier scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

CHAT_JID=$(curl -sS -H "Authorization: Bearer $TIMELINES_AI_API_KEY" \
skills/whatsapp-lead-qualifier/SKILL.md · 198 lines

How it starts

The opening of the file, as written. The whole thing — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.

WhatsApp lead qualifier

This is the canonical example of a multi-turn WhatsApp skill that doesn't need an external state store. State lives on the TimelinesAI chat — as labels for discrete stages, notes for structured answers — and the skill reads it from the chat on every invocation.

State model

What Where Example
Current stage Chat label discovery/q1, discovery/q2, discovery/q3, qualified, disqualified
Collected answers Chat notes [LEAD] use_case=onboarding, [LEAD] team_size=8, [LEAD] timeline=2_weeks
Stop-reply Chat label escalate, needs-human, pause-bot

The labels are the state machine. The notes are the data. Together they replace any external database for this flow.

Question sequence

q1: "What are you trying to solve?"           → answer stored as [LEAD] use_case=...
q2: "How big is your team?"                   → answer stored as [LEAD] team_size=...
q3: "When do you want to start?"              → answer stored as [LEAD] timeline=...

At the end of q3, the skill applies a qualification rule — default is team_size >= 5. Customize this in step 5 below.

Loop

You receive a webhook payload with the incoming customer message. Run these steps in order:

Step 1 — Verify chat ownership

Same as every other send-capable skill. Skip if the chat's whatsapp_account_id doesn't match $ALLOWED_SENDER_JID.

CHAT_JID=$(curl -sS -H "Authorization: Bearer $TIMELINES_AI_API_KEY" \
  "https://app.timelines.ai/integrations/api/chats/$CHAT_ID" \
  | jq -r '.data.whatsapp_account_id')

[ "$CHAT_JID" != "$ALLOWED_SENDER_JID" ] && exit 0

Step 2 — Read the current stage

LABELS=$(curl -sS -H "Authorization: Bearer $TIMELINES_AI_API_KEY" \
  "https://app.timelines.ai/integrations/api/chats/$CHAT_ID/labels" \
  | jq -r '.data.labels[]? // empty')

# Stop entirely if already finished or handed off to a human
case "$LABELS" in
  *qualified*|*disqualified*|*escalate*|*needs-human*|*pause-bot*)
    echo "lead already resolved or paused — exiting"
    exit 0
    ;;
esac

# Find the current discovery stage label
STAGE=$(echo "$LABELS" | grep -oE 'discovery/q[123]' | head -1)

Read the full file on GitHub · 198 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 198 lines · 96 tokens per session scan A 19e4226a546b

Subscribe to this mod's changes

whatsapp-lead-qualifier is a skill published in the GitHub repository InitechSoftware/openclaw-whatsapp-skills (3 stars, last pushed 4mo ago), licensed MIT. It adds 96 tokens to every session and 2,473 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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