Funding Signal Monitor Agent Skill

Funding Signal Monitor

Detect recently-funded startups as buying signals. When a company raises a round, they have fresh capital, aggressive growth plans, and urgent needs for tools and services. This skill finds those companies across multiple sources, qualifies them, and outputs a ranked list ready for outreach.

Why This Works

When a company announces funding, they've:

• Received capital earmarked for growth (hiring, tooling, infrastructure)
• Committed to investors on aggressive milestones
• Entered a 12-18 month sprint to hit next-stage metrics
• Begun evaluating vendors immediately (the "post-raise buying window" is 1-3 months)

Series A-C companies are the sweet spot: enough money to buy, small enough to move fast.

Cost

| Component | Cost |

|-----------|------|

| Web Search (WebSearch tool) | Free |

| Hacker News (Algolia API) | Free |

| Twitter scraper (Apify) | ~$0.05-0.10 per run |

| Reddit scraper (Apify) | ~$0.05-0.10 per run |

Typical run: $0.10-0.20 total. Web Search + HN are free and provide the bulk of results.

Setup

1. Dependencies

pip3 install requests

2. Apify API Token (for Twitter/Reddit scrapers)

export APIFY_API_TOKEN="apify_api_YOUR_TOKEN_HERE"

Not required if you only want Web Search + HN results.

Usage

Phase 1: Configuration

Accept parameters from the user:

| Parameter | Required | Default | Description |

|-----------|----------|---------|-------------|

| target-stages | Yes | — | Comma-separated: "Series A, Series B, Series C" |

| target-industries | No | all | Filter: "SaaS, AI, fintech, healthtech" |

| min-amount | No | none | Minimum raise amount (e.g., "$5M") |

| lookback-days | No | 7 | How far back to search |

| output-path | No | stdout | Where to save the markdown report |

Phase 2: Multi-Source Search

Run these searches in parallel to maximize coverage:

A) Web Search (WebSearch tool)

Run 4-6 queries using the WebSearch tool. Vary the phrasing to catch different announcement styles:

• "Series A announced this week 2026"
• "Series B funding round 2026"
• "startup raised Series A"
• "seed funding announcement startup"
• "[industry] startup funding" (if industry filter specified)
• "raised $" AND "Series" AND "2026"

For each result, extract:

• Company name
• Amount raised
• Stage (Seed, A, B, C, etc.)
• Date of announcement
• Lead investors

B) Twitter Search (twitter-mention-tracker)

python3 skills/twitter-mention-tracker/scripts/search_twitter.py \
  --query "\"excited to announce\" AND (\"raised\" OR \"Series A\" OR \"Series B\" OR \"funding\")" \
  --since <7-days-ago> --until <today> --max-tweets 50 --output json

Funding announcements often break on Twitter first. Founders post "excited to announce" or "thrilled to share" when rounds close.

C) Hacker News (funding-signal-monitor helper script)

python3 skills/funding-signal-monitor/scripts/search_funding.py \
  --stages "Series A,Series B" --days 7 --min-points 5 --output json

Or use the hacker-news-scraper directly:

python3 skills/hacker-news-scraper/scripts/search_hn.py \
  --query "raised funding Series" --days 7 --output json

D) Reddit Search (reddit-post-finder)

python3 skills/reddit-post-finder/scripts/search_reddit.py \
  --subreddit "startups,SaaS,technology" \
  --keywords "raised,Series A,Series B,funding round" \
  --days 7 --sort hot --output json

Phase 3: Consolidation & Qualification

After collecting results from all sources:

• Deduplicate across sources. Same company appearing in multiple sources = higher confidence signal.

• For each company, assess:

| Criterion | How to Evaluate |

|-----------|----------------|

| Stage | Seed, A, B, C, or later — must match target-stages |

| Amount raised | Parse from announcement — filter by min-amount if specified |

| Industry | Infer from company description — filter if target-industries specified |

| Cloud likelihood | Tech/SaaS/AI companies = high; traditional industries = lower |

| Team size estimate | Series A = 10-30, Series B = 30-100, Series C = 100-300 |

| Recency | More recent = more urgent buying window |

• Score each company:
• +3 points: Appears in multiple sources
• +2 points: Stage matches target exactly
• +2 points: Industry matches target
• +1 point: High cloud likelihood (tech/SaaS/AI)
• +1 point: Announced within last 3 days
• -1 point: Stage is outside target range
• -2 points: Non-tech industry (unless specifically targeted)

• Rank by score descending.

Phase 4: Output

Produce a ranked report with the following columns:

| Column | Description |

|--------|-------------|

| Rank | Score-based ranking |

| Company | Company name |

| Amount | Amount raised |

| Stage | Funding stage |

| Date | Announcement date |

| Investors | Lead investors |

| Industry | Company's industry/vertical |

| Source(s) | Where the signal was found (web, Twitter, HN, Reddit) |

| Cloud Likelihood | High / Medium / Low |

| Outreach Angle | Suggested approach based on stage and industry |

Outreach angle templates:

• "Scale fast with fresh capital" — Best for Series A. They're building the team and need tools to move fast before the money runs out.
• "Operationalize before the next round" — Best for Series B. They need to professionalize processes before Series C diligence.
• "Enterprise-ready at scale" — Best for Series C. They're going upmarket and need enterprise-grade tooling.

Save to the specified output path as markdown, or print to stdout.

Optionally export to Google Sheet using the google-sheets-write capability.

Helper Script

A standalone Python script is included for searching Hacker News specifically for funding signals:

# Search HN for Series A and B announcements in last 7 days
python3 skills/funding-signal-monitor/scripts/search_funding.py \
  --stages "Series A,Series B" --days 7 --output json

# Filter to high-engagement posts only
python3 skills/funding-signal-monitor/scripts/search_funding.py \
  --stages "Series A,Series B,Series C" --days 14 --min-points 10 --output text

# Search all stages with industry keyword
python3 skills/funding-signal-monitor/scripts/search_funding.py \
  --stages "Series A" --days 7 --keywords "AI,fintech" --output json

AI Agent Integration

When using this skill as an agent, the typical flow is:

• User specifies target stages, optional industry filter, optional min amount
• Agent runs multi-source search (Phase 2) in parallel
• Agent consolidates and scores results (Phase 3)
• Agent presents ranked list with outreach angles
• User selects companies to pursue
• Agent chains to company-contact-finder to find decision-makers
• Agent chains to cold-email-outreach to launch outreach

Example prompt:

> "Find companies that raised Series A or B in the last week. Focus on SaaS and AI companies. We sell developer tools."

The agent should:

• Run all source searches
• Consolidate and score
• Present the top 10-15 companies with reasoning
• Suggest next steps (find contacts, launch outreach)

The agent should NOT:

• Do any outreach without user confirmation
• Skip the scoring/qualification step
• Rely on a single source (multi-source coverage is the point)

Tips

• Run weekly for best coverage. Funding announcements have a ~1 week news cycle.
• Combine with company-contact-finder to get CTO/VP Eng contacts at funded companies.
• Chain into cold-email-outreach for automated outreach with funding-specific angles.
• Track hits in contact-cache to avoid duplicate outreach across weeks.
• Web Search is your best source — it aggregates TechCrunch, Crunchbase, VentureBeat, etc. Twitter and HN provide supplementary signals and early detection.
• Multi-source appearances are the strongest signal. A company that shows up on TechCrunch AND Hacker News AND Twitter is a higher-quality lead.

Troubleshooting

"No results found"

• Broaden your stages (add Seed or Series C)
• Extend lookback to 14 or 30 days
• Remove industry filter
• Check that scraper dependencies are installed

"Too many results"

• Add an industry filter
• Increase min-amount
• Reduce lookback days
• Focus on Series B+ (fewer but larger rounds)

"Twitter scraper failing"

• Check APIFY_API_TOKEN is set
• Fall back to Web Search + HN only (still effective)
• Twitter is supplementary — the skill works without it

Links

• HN Algolia API
• Apify Console
• Crunchbase (for manual verification)