Skip to content
cccskills
FreePublished on GitHub

account-research

Research companies and people before outreach or meetings. Combines business profiles, recent news, hiring signals, and key contacts into a sourced brief with talking points and suggested questions, adding relationship history when CRM data is connected.

OriginalShow the original description

Get a complete picture of any company or person before outreach. This skill always works with web search, and gets significantly better with enrichment and CRM data.

See how to install

Good for

  • Research a prospective customer before outreach
  • Prepare background information for meeting attendees
  • Compare a competitor's products and positioning
  • Answer account questions using connected internal sources

Files included (1)

  • SKILL.md10.4 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Account Research

Get a complete picture of any company or person before outreach. This skill always works with web search, and gets significantly better with enrichment and CRM data.

How It Works

┌─────────────────────────────────────────────────────────────────┐
│                     ACCOUNT RESEARCH                             │
├─────────────────────────────────────────────────────────────────┤
│  ALWAYS (works standalone via web search)                        │
│  ✓ Company overview: what they do, size, industry               │
│  ✓ Recent news: funding, leadership changes, announcements      │
│  ✓ Hiring signals: open roles, growth indicators                │
│  ✓ Key people: leadership team from LinkedIn                    │
│  ✓ Product/service: what they sell, who they serve              │
├─────────────────────────────────────────────────────────────────┤
│  SUPERCHARGED (when you connect your tools)                      │
│  + Enrichment: verified emails, phone, tech stack, org chart    │
│  + CRM: prior relationship, past opportunities, contacts        │
└─────────────────────────────────────────────────────────────────┘

Getting Started

Just tell me who to research:

  • "Research Stripe"
  • "Look up the CTO at Notion"
  • "Intel on acme.com"
  • "Who is Sarah Chen at TechCorp?"
  • "Tell me about [company] before my call"

I'll run web searches immediately. If you have enrichment or CRM connected, I'll pull that data too.


Connectors (Optional)

Connect your tools to supercharge this skill:

ConnectorWhat It Adds
EnrichmentVerified emails, phone numbers, tech stack, org chart, funding details
CRMPrior relationship history, past opportunities, existing contacts, notes

No connectors? No problem. Web search provides solid research for any company or person.


Output Format

# Research: [Company or Person Name]

**Generated:** [Date]
**Sources:** Web Search [+ Enrichment] [+ CRM]

---

## Quick Take

[2-3 sentences: Who they are, why they might need you, best angle for outreach]

---

## Company Profile

| Field | Value |
|-------|-------|
| **Company** | [Name] |
| **Website** | [URL] |
| **Industry** | [Industry] |
| **Size** | [Employee count] |
| **Headquarters** | [Location] |
| **Founded** | [Year] |
| **Funding** | [Stage + amount if known] |
| **Revenue** | [Estimate if available] |

### What They Do
[1-2 sentence description of their business, product, and customers]

### Recent News
- **[Headline]** — [Date] — [Why it matters for your outreach]
- **[Headline]** — [Date] — [Why it matters]

### Hiring Signals
- [X] open roles in [Department]
- Notable: [Relevant roles like Engineering, Sales, AI/ML]
- Growth indicator: [Hiring velocity interpretation]

---

## Key People

### [Name] — [Title]
| Field | Detail |
|-------|--------|
| **LinkedIn** | [URL] |
| **Background** | [Prior companies, education] |
| **Tenure** | [Time at company] |
| **Email** | [If enrichment connected] |

**Talking Points:**
- [Personal hook based on background]
- [Professional hook based on role]

[Repeat for relevant contacts]

---

## Tech Stack [If Enrichment Connected]

| Category | Tools |
|----------|-------|
| **Cloud** | [AWS, GCP, Azure, etc.] |
| **Data** | [Snowflake, Databricks, etc.] |
| **CRM** | [e.g. Salesforce, HubSpot] |
| **Other** | [Relevant tools] |

**Integration Opportunity:** [How your product fits with their stack]

---

## Prior Relationship [If CRM Connected]

| Field | Detail |
|-------|--------|
| **Status** | [New / Prior prospect / Customer / Churned] |
| **Last Contact** | [Date and type] |
| **Previous Opps** | [Won/Lost and why] |
| **Known Contacts** | [Names already in CRM] |

**History:** [Summary of past relationship]

---

## Qualification Signals

### Positive Signals
- ✅ [Signal and evidence]
- ✅ [Signal and evidence]

### Potential Concerns
- ⚠️ [Concern and what to watch for]

### Unknown (Ask in Discovery)
- ❓ [Gap in understanding]

---

## Recommended Approach

**Best Entry Point:** [Person and why]

**Opening Hook:** [What to lead with based on research]

**Discovery Questions:**
1. [Question about their situation]
2. [Question about pain points]
3. [Question about decision process]

---

## Sources
- [Source 1](URL)
- [Source 2](URL)

Execution Flow

Step 1: Parse Request

Identify what to research:
- "Research Stripe" → Company research
- "Look up John Smith at Acme" → Person + company
- "Who is the CTO at Notion" → Role-based search
- "Intel on acme.com" → Domain-based lookup

Step 2: Web Search (Always)

Run these searches:
1. "[Company name]" → Homepage, about page
2. "[Company name] news" → Recent announcements
3. "[Company name] funding" → Investment history
4. "[Company name] careers" → Hiring signals
5. "[Person name] [Company] LinkedIn" → Profile info
6. "[Company name] product" → What they sell
7. "[Company name] customers" → Who they serve

Extract:

  • Company description and positioning
  • Recent news (last 90 days)
  • Leadership team
  • Open job postings
  • Technology mentions
  • Customer base

Step 3: Enrichment (If Connected)

If enrichment tools available:
1. Enrich company → Firmographics, funding, tech stack
2. Search people → Org chart, contact list
3. Enrich person → Email, phone, background
4. Get signals → Intent data, hiring velocity

Enrichment adds:

  • Verified contact info
  • Complete org chart
  • Precise employee count
  • Detailed tech stack
  • Funding history with investors

Step 4: CRM Check (If Connected)

If CRM available:
1. Search for account by domain
2. Get related contacts
3. Get opportunity history
4. Get activity timeline

CRM adds:

  • Prior relationship context
  • What happened before (won/lost deals)
  • Who we've talked to
  • Notes and history

Step 5: Synthesize

1. Combine all sources
2. Prioritize enrichment data over web (more accurate)
3. Add CRM context if exists
4. Identify qualification signals
5. Generate talking points
6. Recommend approach

Research Variations

Company Research

Focus on: Business overview, news, hiring, leadership

Person Research

Focus on: Background, role, LinkedIn activity, talking points

Competitor Research

Focus on: Product comparison, positioning, win/loss patterns

Pre-Meeting Research

Focus on: Attendee backgrounds, recent news, relationship history


Tips for Better Research

  1. Include the domain — "research acme.com" is more precise
  2. Specify the person — "look up Jane Smith, VP Sales at Acme"
  3. State your goal — "research Stripe before my demo call"
  4. Ask for specifics — "what's their tech stack?" after initial research

Answering Internal Questions About an Account (When Internal Tools Are Connected)

The flow above is for building a picture of a company or person before outreach. Sometimes the ask is different: answering a specific question about an existing customer or account, where internal sources (docs, wiki, CRM, support tickets, chat, email) matter as much as or more than the public web. When internal tools are connected, apply this source hierarchy and confidence discipline instead of treating every source as equally trustworthy.

Source Tiers (Decreasing Authority)

  1. Official internal sources — product documentation, knowledge base/wiki, policy documents, roadmap. Confidence: High, unless clearly outdated.
  2. Organizational context — CRM notes, support tickets, internal docs, meeting notes. Confidence: Medium-High — may reflect one perspective.
  3. Team communications — chat history, email threads, calendar notes. Confidence: Medium — informal, may be out of context.
  4. External sources — web search, forums, third-party docs, news/analyst reports. Confidence: Low-Medium — not authoritative for internal matters.
  5. Inferred or analogical — similar past situations, analogous accounts, general best practices. Confidence: Low — flag explicitly as inference, not fact.

Search in priority order, but don't stop at the first hit — cross-reference across tiers before answering.

Confidence Levels to State Explicitly

  • High — confirmed by an official/authoritative source, or corroborated by multiple sources, and current.
  • Medium — found in informal sources without corroboration, or possibly slightly stale.
  • Low — inferred from related information, sources are outdated or conflicting.
  • Unable to determine — no relevant information found; say so and name who to ask.

When sources disagree: note the contradiction, identify which is more authoritative/recent, present both with context, and default to the most conservative answer if it's going to a customer.

When to Escalate Instead of Answering Directly

Escalate or verify before answering when the question involves roadmap commitments, pricing/legal/contract terms, security/compliance/data handling, could set a precedent, has contradictory source data, involves a specific customer's custom configuration, or the account is at risk. Otherwise — clear docs, corroborated by multiple sources, factual and non-sensitive — answer directly.

Capture It for Next Time

If the question took real effort to answer, is likely to recur, or corrects a common misunderstanding, write it up (question, confidence, answer, sources, review notes) into the team's knowledge base rather than letting the research evaporate after this one reply.


Related Skills

  • call-prep — Full meeting prep with this research plus context
  • draft-outreach — Write personalized message based on research
  • prospecting — Qualify and prioritize research targets

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

access-policy

FreeSummary

Review Slack access requests against Okta role and team information, then prepare narrowly scoped GitHub or AWS IAM permissions. Apply changes only after an eligible person's approval and record the grant, reasoning, approver, and timestamp.

  • Reviewing GitHub repository access requests from Slack
  • Preparing AWS IAM permissions for a specific task
  • Routing sensitive access requests for additional review
kortix-ai/suna20.3KUpdated Oct 18, 2026

Review daily Google Ads and Meta Ads results for budget pacing, declining performance, and unusual activity. Get prioritized findings with supporting numbers and concrete recommendations for a marketing team to assess and carry out.

  • Checking whether campaign budgets are being spent on schedule
  • Investigating rising acquisition costs or falling ad returns
  • Finding ads and keywords that spend without converting
kortix-ai/suna20.3KUpdated Oct 18, 2026

agent-browser

FreeSummary

Automate website tasks such as navigating pages, filling forms, clicking buttons, taking screenshots, and extracting data. The skill also supports web app testing, with specialized guides for Electron desktop apps, Slack, and cloud browsers.

  • Automate form entry and page navigation
  • Capture screenshots and extract page data
  • Explore web apps for bugs
kortix-ai/suna20.3KUpdated Oct 18, 2026

ap-invoice-match

FreeSummary

Process emailed vendor invoices by extracting details, comparing them with purchase orders and invoice history, and recording duplicates, overcharges, or missing orders. Summarize results in Slack for human review; payment approval and execution remain with people.

  • Checking incoming invoices against purchase orders
  • Finding duplicate invoices and likely resends
  • Reviewing unit prices and remaining order balances
kortix-ai/suna20.3KUpdated Oct 18, 2026

billing

FreeSummary

Guide changes to Kortix billing code, admin controls, and pricing screens. Explain how plans, trials, enterprise contracts, and access exceptions should work, where pricing is defined, and which audited routes must handle account changes.

  • Update billing logic and its specification together
  • Review how trials and enterprise contracts are handled
  • Find the code that defines prices and allowances
kortix-ai/suna20.3KUpdated Oct 18, 2026

Monitor public news, social platforms, and forums for new brand mentions. Remove previously reported results, classify sentiment, and send a Slack digest with response drafts for negative or notable mentions, leaving public replies to people.

  • Track new brand mentions each day
  • Identify negative or widely seen mentions
  • Prepare response drafts for human review
kortix-ai/suna20.3KUpdated Oct 18, 2026

See all skills by kortix-ai

Report a problem with this skill