A sales-research tool for investigating a target company and preparing personalized business-to-business outreach.

Use it when prospecting a company, researching a target account, or drafting a personalized sales email; it requires the company name and website.

It combines account research, contact identification, and a draft cold email for a specific company.

b2b-sales — Skill for Claude Code and Codex by ebenezer-isaac

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 ebenezer-isaac/llmconveyors-mcp --skill b2b-sales

Clone the repo

git clone --depth 1 https://github.com/ebenezer-isaac/llmconveyors-mcp

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/ebenezer-isaac/llmconveyors-mcp/b2b-sales/github.svg)](https://agentmods.dev/skills/ebenezer-isaac/llmconveyors-mcp/b2b-sales)

Your own site

<a href="https://agentmods.dev/skills/ebenezer-isaac/llmconveyors-mcp/b2b-sales"><img src="https://agentmods.dev/badge/skills/ebenezer-isaac/llmconveyors-mcp/b2b-sales/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/ebenezer-isaac/llmconveyors-mcp/b2b-sales"><img src="https://agentmods.dev/badge/skills/ebenezer-isaac/llmconveyors-mcp/b2b-sales.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 432 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.

Model	Per session	Once invoked
Fable 5.1	$0.00044	$0.00432
Opus 5	$0.00022	$0.00216
Sonnet 5	$0.00009	$0.00086
Haiku 4.5	$0.00004	$0.00043

Measured 12d ago against content hash 0cd320513a45, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

b2b-sales 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.

skills/b2b-sales/SKILL.md · 49 lines

What it actually says

B2B Sales

Research a target company and generate personalized cold email outreach for B2B sales.

When to use

User wants to research a company for sales prospecting
User needs a personalized cold email for a specific company
User mentions B2B outreach, sales emails, or account research
User has a company name and website they want to target

Steps

Get company details. You need: company name and website URL. Ask the user if not provided.
Run the agent. Call b2b-sales-run with:
- companyName - target company name
- companyWebsite - company website URL
- strategy (optional) - specific angle or approach for the outreach
Present the results. The agent returns company research, person research (identifying the right contact), and a drafted cold email. Share these with the user.
Create a share link. If the user wants to share the output, call share-create with the session and generation IDs from the run result.

Example

User: "Research Notion and draft a sales email for our developer tools product"

1. Call b2b-sales-run with companyName="Notion", companyWebsite="https://notion.so", strategy="Focus on developer tools integration"
2. Wait for completion (may take 3-10 minutes)
3. Present the company research report and drafted cold email

Tips

The agent performs deep company research including identifying decision makers
Results typically take 3-10 minutes depending on how much public information is available
The strategy parameter helps focus the outreach angle

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.

12d ago First seen · 49 lines · 44 tokens per session scan A 0cd320513a45

Subscribe to this mod's changes

b2b-sales is a skill published in the GitHub repository ebenezer-isaac/llmconveyors-mcp (1 stars, last pushed 5mo ago), licensed MIT. It adds 44 tokens to every session and 432 once invoked, about $0.0002 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.

Marketing and SEO Research

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens