Agent skill
funding-signal-outreach
Outreach triggered by funding events with post-funding needs analysis and personalized drafts
Filed under Prospecting and list building and Outbound email.
From ekatasingh1107/b2b-gtm-skills · 99 skills · 2 · pushed 2026-04-11
What it does when it runs
Outreach triggered by funding events with post-funding needs analysis and personalized drafts
Read from the skill and the 1 file bundled beside it. A skill’s own description is written to be selected by an agent, so it describes the job and not the dependencies.
- Keys and connectors you must supply
- None found.
- Hosts it reaches
- freshd2c.com
- Tool permissions it declares
- No
allowed-toolsin the frontmatter. It does act, so it runs under whatever permissions your session already grants. - Actions present in the files
- network
Install it
View source on GitHub ↗git clone --depth 1 --filter=blob:none --sparse https://github.com/ekatasingh1107/b2b-gtm-skills.git /tmp/b2b-gtm-skills git -C /tmp/b2b-gtm-skills sparse-checkout set "skills/composites/funding-signal-outreach" mkdir -p ~/.claude/skills/funding-signal-outreach cp -R "/tmp/b2b-gtm-skills/skills/composites/funding-signal-outreach/." ~/.claude/skills/funding-signal-outreach/
Picked up without a restart. A project skill of the same name is shadowed by your personal one. For one repository only, swap ~/.claude/skills for .claude/skills. Claude Code docs ↗
The folder is the same in every client that implements the format — 46 of them — so if yours is not above, only the destination changes.
The skill
Source on GitHub ↗Reproduced in full from ekatasingh1107/b2b-gtm-skills/blob/eae8dd0bb98da1c8e84abd297066a87015dd860f/skills/composites/funding-signal-outreach/SKILL.md, which is licensed MIT (repository). 1,183 words, 11 headings.
Funding Signal Outreach
Monitors and acts on funding announcements from companies matching ICP. For each funded company, researches what they will likely need post-funding, matches needs to agency services, scores timing urgency, and drafts personalized outreach referencing their round. Outputs qualified leads with funding context and ready-to-send messages.
Prerequisites
agency.config.jsonin the project root- WebSearch tool for finding funding announcements
- Optional:
company-researcherfor deep company analysis - Optional:
cold-email-drafterfor polished email generation - Optional:
person-researcherfor finding the right contact
Capabilities Used
company-researcher-- for deep-dive on funded companiesperson-researcher-- for identifying decision-makers at funded companiescold-email-drafter-- for generating polished outreach emailslead-scorer-- for scoring the funded company against ICPcrm-writer-- for logging qualified leads to CRM
Phase 0: Read Config
- Read
agency.config.jsonfrom the project root. - Extract ICP definition:
icp.segments[]-- target segments with industry, size, geographyicp.geography-- target geographiesicp.company_size-- revenue or employee range
- Extract
services[]-- services to match against post-funding needs. - Extract
outreach.toneandoutreach.banned_phrasesfor email drafting. - Extract
case_studies[]for proof points relevant to funded companies. - Check
tools.researchfor data source preferences.
Phase 1: Search for Funding Announcements
Search for recent funding events matching ICP:
Search queries (via WebSearch):
- "[industry] funding announcement [current_month] [current_year]"
- "[industry] Series A OR Series B OR seed round [geography]"
- "D2C brand funding [geography] [current_year]"
- "e-commerce startup funding round [current_month]"
- site:techcrunch.com "[industry] funding [current_year]"
- site:crunchbase.com "[industry] funding rounds"
- "[geography] startup funding news this week"
Additional sources to check:
- Crunchbase recent rounds (via WebSearch:
site:crunchbase.com/funding_round) - TechCrunch funding coverage
- Inc42 (for India), TechInAsia (for Asia)
- Press releases on PR Newswire / BusinessWire
- LinkedIn funding announcements
For each result, extract:
Company: [name]
Round: [Seed / Series A / Series B / etc.]
Amount: $[X]M
Date: [announcement date]
Investors: [lead investor(s)]
Industry: [sector]
Geography: [HQ location]
Website: [URL]
Source: [where we found this]
Phase 2: Filter and Match to ICP
Score each funded company against ICP:
ICP MATCH SCORING
===
Company | Industry Match | Geo Match | Size Match | ICP Score | Status
-----------------|---------------|-----------|------------|-----------|--------
FreshD2C | D2C (exact) | India | Series A | 95/100 | STRONG
GlowSkin | Skincare D2C | US | Seed | 80/100 | GOOD
TechWidget | SaaS (miss) | India | Series B | 30/100 | SKIP
SportyBrand | Sports D2C | UK | Series A | 85/100 | GOOD
Discard companies with ICP score below 50. Proceed with matches.
Phase 3: Post-Funding Needs Analysis
For each qualified company, predict what they need post-funding:
Post-funding need patterns by round:
| Round | Typical Needs | Timing Urgency |
|---|---|---|
| Seed | Brand identity, initial store build, MVP website | HIGH -- building from scratch |
| Series A | Scale operations, revamp website, CRO optimization, marketing | HIGH -- pressure to grow fast |
| Series B | Performance marketing at scale, international expansion, advanced CRO | MEDIUM -- already have some team |
| Series C+ | Enterprise features, custom development, data infrastructure | LOW -- likely have in-house team |
Research each company (via WebSearch and company-researcher):
POST-FUNDING NEEDS ASSESSMENT: [Company Name]
===
Round: Series A ($5M)
Current website: [URL] -- quality assessment
Current Shopify store: [yes/no, theme quality]
Current team size: [N] (check LinkedIn)
Open positions: [roles being hired -- indicates gaps]
Recent press: [what they say they'll use funds for]
Predicted needs:
1. [Need 1 -- e.g., "Store revamp -- current site is basic Shopify theme"]
2. [Need 2 -- e.g., "CRO -- scaling traffic without optimized conversion"]
3. [Need 3 -- e.g., "Catalog management -- expanding from 50 to 200 SKUs"]
Service match:
- [Your service 1] matches need [1] -- relevance: HIGH
- [Your service 2] matches need [2] -- relevance: HIGH
Timing urgency: HIGH (Series A companies typically spend on growth within 3 months of closing)
Phase 4: Score and Rank Leads
Score each lead on:
LEAD SCORING
===
Company | ICP Fit | Funding Recency | Need Match | Timing | Total Score
------------|---------|-----------------|------------|--------|------------
FreshD2C | 95 | 5 days ago | 3 services | HIGH | 92/100
SportyBrand | 85 | 12 days ago | 2 services | HIGH | 85/100
GlowSkin | 80 | 30 days ago | 2 services | MEDIUM | 72/100
Scoring weights:
- ICP fit: 30%
- Funding recency (prefer last 30 days): 25%
- Service need match: 25%
- Timing urgency: 20%
Phase 5: Draft Personalized Outreach
For each qualified lead, draft outreach using the Signal-Proof-Ask framework:
Email structure:
Subject: Congrats on the [round] -- [specific observation]
[Reference the funding]: "Saw [Company] just closed [round] -- congrats.
[Most companies at this stage face X]."
[Match to their need]: "With [amount raised], you're likely [scaling/revamping/expanding].
We've helped [similar company] do exactly that."
[Proof point]: "[Case study result -- specific metric]."
[Soft CTA]: "Worth a quick look at how this could work for [Company]?"
Generate for each lead:
- Email draft (using
cold-email-drafterif available) - LinkedIn connection note (under 300 chars)
- LinkedIn message (if already connected)
Personalization must include:
- The specific round and amount
- A specific observation about their current website/store
- A relevant case study matching their industry
- A specific service recommendation based on their needs
Phase 6: Output
Return structured JSON:
{
"funding_signal_outreach": {
"search_date": "2024-03-15",
"search_criteria": {
"industries": ["D2C", "e-commerce"],
"geographies": ["India", "US", "UK"],
"round_types": ["Seed", "Series A", "Series B"],
"recency": "last 30 days"
},
"funding_events_found": 15,
"icp_matches": 8,
"qualified_leads": [
{
"company": "FreshD2C",
"website": "https://freshd2c.com",
"round": "Series A",
"amount": "$5M",
"date": "2024-03-10",
"investors": ["Sequoia India"],
"icp_score": 92,
"predicted_needs": ["store revamp", "CRO", "catalog management"],
"service_matches": ["Shopify development", "CRO optimization"],
"timing_urgency": "high",
"contacts": [
{
"name": "Founder Name",
"title": "CEO",
"linkedin": "URL",
"email": "[email protected]"
}
],
"outreach": {
"email_subject": "",
"email_body": "",
"linkedin_note": "",
"linkedin_message": ""
}
}
],
"summary": {
"total_qualified": 5,
"total_outreach_drafted": 5,
"top_opportunity": "FreshD2C -- Series A, strong ICP match, 3 service needs"
}
}
}
Log qualified leads to CRM via crm-writer (Researched Leads tab) with source tagged as "funding_signal."
Example Usage
Trigger phrases:
- "Find companies that just raised funding in our ICP"
- "Search for D2C funding announcements this month"
- "Funding signal outreach for this week"
- "Which startups just got funded that we should reach out to?"
- "Find recently funded e-commerce companies in India"
User: Find recently funded D2C companies we should reach out to
Assistant: [searches for D2C funding in last 30 days, finds 15 events, filters to 5 ICP matches, researches each company's website and needs, drafts personalized outreach referencing their specific round and current store gaps, logs to CRM]
User: Any new funding rounds in Indian e-commerce this week?
Assistant: [searches India-focused funding news, finds 3 new rounds, scores against ICP, identifies 2 strong matches, drafts outreach for each with relevant case studies]
Files bundled with it
These load only when the skill asks for them, so they cost nothing until it runs.
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Need help setting it up?
This page tells you what funding-signal-outreach does and what it needs. Cheetah builds the agent setup it runs inside: data, CRM, sequencing and the guardrails.
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