b2b-lead-hunter

b2b-lead-hunter is a skill for Claude Code, Codex from xiongQvQ/-b2b-lead-hunter-skill. It costs 88 tokens per session (3,215 once invoked), scanned A, original, MIT.

A workflow for finding foreign-trade business prospects such as importers, distributors, wholesalers, and buyer companies. It also gathers evidence, contact routes, and information about relevant decision makers.

In plain words
What is it for?
Use it to research export leads from a product, region, target-customer profile, website, or document; identify contact emails and decision makers; score prospects; and prepare outreach files and email drafts.
Why use it?
It reduces the manual work of searching for suitable companies, checking whether they fit a target market, finding people to contact, and keeping sources attached to each result.

Skill for Claude CodeCodex

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

Good fit Use it to research export leads from a product, region, target-customer profile, website, or document; identify contact emails and decision makers; score prospects; and prepare outreach files and email drafts.

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Install with agentmods
npx agentmods add skills/xiongqvq/-b2b-lead-hunter-skill/b2b-lead-hunter-skill
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 xiongQvQ/-b2b-lead-hunter-skill --skill b2b-lead-hunter-skill
Clone the repo
git clone --depth 1 https://github.com/xiongQvQ/-b2b-lead-hunter-skill

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 b2b-lead-hunter

README.md
[![agentmods](https://agentmods.dev/badge/skills/xiongqvq/-b2b-lead-hunter-skill/b2b-lead-hunter-skill/github.svg)](https://agentmods.dev/skills/xiongqvq/-b2b-lead-hunter-skill/b2b-lead-hunter-skill)
Your own site
<a href="https://agentmods.dev/skills/xiongqvq/-b2b-lead-hunter-skill/b2b-lead-hunter-skill"><img src="https://agentmods.dev/badge/skills/xiongqvq/-b2b-lead-hunter-skill/b2b-lead-hunter-skill/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 b2b-lead-hunter

Your own site · 80×15
<a href="https://agentmods.dev/skills/xiongqvq/-b2b-lead-hunter-skill/b2b-lead-hunter-skill"><img src="https://agentmods.dev/badge/skills/xiongqvq/-b2b-lead-hunter-skill/b2b-lead-hunter-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 88 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,215 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 $0.00088 $0.03215
Opus 5 $0.00044 $0.01607
Sonnet 5 $0.00018 $0.00643
Haiku 4.5 $0.00009 $0.00321

Measured 12d ago against content hash 8443a4b35047, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

b2b-lead-hunter 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 12d 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.

SKILL.md · 265 lines

How it starts

The opening of the file, as written. The whole thing — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.

B2B Lead Hunter

Purpose

Research foreign-trade B2B prospects and contact channels for physical-product export, distributor discovery, importer discovery, and outreach preparation.

Hermes owns judgment, evidence review, search iteration, language choice, and approval decisions. Scripts own deterministic normalization, page reading, contact extraction, dedupe, validation, template rendering, draft evaluation, export, and SMTP plumbing.

Default objective: produce a traceable lead file where every company, contact channel, decision maker, score, and outreach draft is tied to source URLs and structured artifacts. Quality gates override target count.

User Workflow Preference

User prefers continuous-cycle execution: mine leads → find decision makers → generate emails → send, all in one loop. Do not pause between stages unless the user explicitly asks to stop. After sending one batch, immediately resume mining the next. The cycle is:

search new leads → get contact emails → send generic emails
    → search decision makers → infer/find DM emails → send DM emails
    → search new leads (next country/niche) → repeat

Do not ask "continue or pause?" after each batch — just keep going until the user says stop.

Non-Negotiable Rules

  • Use scripts/read_jina.py as the primary reader for every website or URL: seller site, candidate website, contact page, product page, directory profile, or source article. Use browser tools only when Jina fails or interaction is required.
  • Use Hermes native web search for search queries. Do not open Google, Bing, or other search engines in a browser.
  • Keep lead discovery, outreach drafting, human approval, and SMTP sending as separate stages with separate files.
  • Do not send email unless the user explicitly requests sending, SMTP config exists, approved records exist, suppression checks run, and send_smtp.py receives matching passing evaluations.
  • Never auto-send to inferred emails, free-mail addresses, low/reject leads, directory-only leads, records without source URLs, or records without buyer-role evidence.
  • A lead cannot enter strict leads.csv unless company reality, buyer-role evidence, contactability, and source URLs are present.
  • Do not relax gates to satisfy target_count.
  • Directories and B2B platforms are discovery sources, not final truth. Confirm with official or strong independent evidence before accepting.
  • Customs/trade evidence is useful buying intent, but absence of customs data is not a rejection reason.
  • Every outreach message must include truthful sender identity, source-backed personalization, a low-pressure CTA, and a clear opt-out line.

Read the full file on GitHub · 265 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. 12d ago First seen · 265 lines · 88 tokens per session scan A 8443a4b35047

Subscribe to this mod's changes

b2b-lead-hunter is a skill published in the GitHub repository xiongQvQ/-b2b-lead-hunter-skill (30 stars, last pushed 3mo ago), licensed MIT. It adds 88 tokens to every session and 3,215 once invoked, about $0.0004 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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