account-research
Gather actionable sales intelligence on companies and individuals before outreach
Best use case
account-research is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Gather actionable sales intelligence on companies and individuals before outreach
Teams using account-research should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/account-research/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How account-research Compares
| Feature / Agent | account-research | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Gather actionable sales intelligence on companies and individuals before outreach
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Account Research Skill Overview The **account-research** skill enables you to gather actionable sales intelligence on companies and individuals before outreach. It operates in three tiers: ## Core Functionality **Always Available (Web Search):** The skill conducts automatic web searches to compile company overviews, recent news, hiring signals, key personnel, and product information. You activate it with triggers like "Research [company]" or "Look up [person]." **Supercharged (With Connectors):** When you connect enrichment tools or CRM systems, the skill gains access to verified contact details, technology stacks, organizational charts, prior relationship history, and opportunity records. ## Research Output Results follow a structured format including: - Quick assessment of relevance and outreach angle - Company profile with foundational details - Recent news tied to sales implications - Leadership team information with talking points - Technology stack details (when enrichment connected) - Prior relationship context (when CRM connected) - Qualification signals highlighting strengths and concerns - Recommended entry points and discovery questions ## Execution Process The skill sequences five steps: parsing your request, conducting web searches, pulling enrichment data if available, checking CRM history if connected, and synthesizing all sources into actionable intelligence. **Best Practice:** Include specific domains or full names for more precise results.
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