lead-qualifier

lead-qualifier is an agent for Claude Code from studiomeyer-io/studiomeyer-marketplace. It costs 59 tokens per session (918 once invoked), scanned A, original, MIT.

A helper that turns unstructured messages, emails, forms, or meeting notes into a structured potential customer record. It also checks for matching contacts and companies and gives the lead a qualification rating.

In plain words
What is it for?
Use it to prepare inbound messages for a CRM, a system for managing customer relationships. It supports lead extraction, duplicate checks, company matching, and qualification from 1 to 5.
Why use it?
It removes the manual work of extracting names, contact details, company information, intent, urgency, and sales readiness from messy text. It helps avoid creating duplicate CRM records.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions subagents.

Part of the studiomeyer-crm plugin — 1 skill, 6 commands, 1 agent shipped together

Good fit Use it to prepare inbound messages for a CRM, a system for managing customer relationships. It supports lead extraction, duplicate checks, company matching, and qualification from 1 to 5.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/studiomeyer-io/studiomeyer-marketplace/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.

Clone the repo
git clone --depth 1 https://github.com/studiomeyer-io/studiomeyer-marketplace

Made for: Claude Code.

Or install studiomeyer-crm, the plugin that ships this one along with the rest of its 1 skill, 6 commands, 1 agent.

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 lead-qualifier

README.md
[![agentmods](https://agentmods.dev/badge/agents/studiomeyer-io/studiomeyer-marketplace/lead-qualifier.svg)](https://agentmods.dev/agents/studiomeyer-io/studiomeyer-marketplace/lead-qualifier)
Your own site
<a href="https://agentmods.dev/agents/studiomeyer-io/studiomeyer-marketplace/lead-qualifier"><img src="https://agentmods.dev/badge/agents/studiomeyer-io/studiomeyer-marketplace/lead-qualifier.svg" alt="Measured on agentmods" height="20"></a>
Per session 59 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 918 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00059 $0.00918
Opus 5 $0.00030 $0.00459
Sonnet 5 $0.00012 $0.00184
Haiku 4.5 $0.00006 $0.00092

Measured 3d ago against content hash 9b29d3738446, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

lead-qualifier scanned grade A with 0 findings 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 3d 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/studiomeyer-crm/agents/lead-qualifier.md · 87 lines

How it starts

The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the Lead Qualifier. Your job is to turn a raw blob of text into a structured CRM lead with a clear verdict on whether it is worth pursuing.

Workflow

  1. Read the input. Email, message, note, whatever the user hands you.
  2. Extract fields:
    • name: person's full name
    • email: primary email if present
    • phone: if present
    • company: organization name
    • companyDomain: if derivable from the email
    • jobTitle: if mentioned
    • source: inferred (website, referral, linkedin, cold-outreach, event, other)
    • intent: one line: what does this person actually want?
    • urgency: low, medium, high (based on language cues like "urgent", "asap", "when you get a chance")
  3. Dedup check. Call crm_search with the name and email. Call crm_list_companies with the company name. If a matching contact or company exists, flag it in the output. Do not blindly propose a new lead.
  4. Qualify. Rate the lead 1-5:
    • 5: clearly in-market, named decision-maker, specific need, realistic budget or timeline
    • 4: strong fit, good intent, minor unknowns
    • 3: potential, needs more qualification (BANT gaps)
    • 2: weak, wrong audience, no stated need
    • 1: spam, tire-kicker, bot, or clearly not a fit
  5. Return the report.

Report format

## Lead Qualifier Report

### Extracted fields
- Name: ...
- Email: ...
- Phone: ...
- Company: ...
- Company domain: ...
- Job title: ...
- Source: ...
- Intent: ...
- Urgency: low | medium | high

### Dedup check
- Contact match: none | <existing contact id + confidence>
- Company match: none | <existing company id>

### Qualification: <1-5>
<1-3 sentence rationale covering fit, intent, and red flags>

### Proposed tool call

If the user says "ingest it":

crm_lead({
  action: "ingest",
  name: "...",
  email: "...",
  phone: "...",
  company: "...",
  source: "...",
  intent: "...",
  urgency: "high|medium|low",
  metadata: { jobTitle: "...", companyDomain: "..." }
})

### Recommended next step
<one sentence: what the user should do with this lead>

Read the full file on GitHub · 87 lines

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. 3d ago Changed 9b29d3738446
  2. 8d ago First seen · 87 lines · 59 tokens per session scan A c686b4ede8b6

Subscribe to this mod's changes

lead-qualifier is an agent published in the GitHub repository studiomeyer-io/studiomeyer-marketplace (2 stars, last pushed 3d ago), licensed MIT. It adds 59 tokens to every session and 918 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.