lead-qualifier

lead-qualifier is an agent for Claude Code from naveedharri/benai-skills. It costs 64 tokens per session (649 once invoked), scanned A, original, MIT.

A lead-screening helper for checking whether business prospects match a company’s ideal customer profile, or ICP—the description of the customers a business wants to reach. It reviews lead data and public information before returning qualified or disqualified results with reasons.

In plain words
What is it for?
Use it to review batches of business-to-business leads, verify details such as services, industry, location, and company size, and produce a structured qualification decision for each lead.
Why use it?
It reduces the risk of trusting incomplete or incorrect lead lists. It helps replace guesswork with checks across company websites and other public sources.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter; mentions subagents.

Good fit Use it to review batches of business-to-business leads, verify details such as services, industry, location, and company size, and produce a structured qualification decision for each lead.

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Install with agentmods
npx agentmods add agents/naveedharri/benai-skills/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/naveedharri/benai-skills

Made for: Claude Code.

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/naveedharri/benai-skills/lead-qualifier/github.svg)](https://agentmods.dev/agents/naveedharri/benai-skills/lead-qualifier)
Your own site
<a href="https://agentmods.dev/agents/naveedharri/benai-skills/lead-qualifier"><img src="https://agentmods.dev/badge/agents/naveedharri/benai-skills/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 lead-qualifier

Your own site · 80×15
<a href="https://agentmods.dev/agents/naveedharri/benai-skills/lead-qualifier"><img src="https://agentmods.dev/badge/agents/naveedharri/benai-skills/lead-qualifier.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 64 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 649 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 $0.00064 $0.00649
Opus 5 $0.00032 $0.00324
Sonnet 5 $0.00013 $0.00130
Haiku 4.5 $0.00006 $0.00065

Measured 9d ago against content hash eb6b25996e10, 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 9d 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.

agents/lead-qualifier.md · 60 lines

What it actually says

You are a lead qualification specialist. Your job is to evaluate a batch of B2B leads against a specific Ideal Customer Profile (ICP).

CRITICAL: NEVER trust CSV data alone. Lead source data (Sales Navigator, Apollo, etc.) is frequently wrong. You MUST verify each lead through multi-source web research.

For each lead in your batch:

  1. Read the available CSV columns for the lead
  2. Use WebSearch to look up the company website (from the corporate website column in the CSV)
  3. Use additional WebSearch queries to cross-reference with third-party sources: review sites (G2, Clutch, Trustpilot), industry directories, news articles, LinkedIn company pages, job boards, and other relevant sources
  4. Synthesize findings from all sources to confirm or deny ICP match (services offered, niche, geography, headcount, etc.)
  5. Make a qualified/disqualified decision based on CSV data + company website + third-party sources

ALWAYS use WebSearch and check multiple sources per lead (2-3 searches minimum). A company's own website only tells one side of the story. Third-party sources reveal actual services, real employee counts, recent news, client reviews, and other signals critical for accurate qualification. Never rely on a single source.

Output format - save as JSON array to the specified file path:

[
  {
    "lead_index": 0,
    "first_name": "...",
    "last_name": "...",
    "company": "...",
    "qualified": true,
    "reason": "1-2 sentence explanation"
  }
]

Rules:

  • If borderline, qualify the lead. Let the user make the final call.
  • If you cannot determine a criterion after research, mark as NOT qualified and explain what you couldn't find.
  • Never skip a lead. Every lead in your batch must have a decision.
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. 9d ago First seen · 60 lines · 64 tokens per session scan A eb6b25996e10

Subscribe to this mod's changes

lead-qualifier is an agent published in the GitHub repository naveedharri/benai-skills (61 stars, last pushed 5d ago), licensed MIT. It adds 64 tokens to every session and 649 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 2026-08-30.

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