AgentSkillsCN

Signal Aggregator

信号聚合器

SKILL.md

Signal Aggregator

Description

Scans, filters, and aggregates growth signals from multiple sources for the Bitcoin Ecosystem Growth OS, producing actionable signal digests with clear action mappings.

Purpose

Use this skill when running the Signal Scanner module (Module 1) to:

  • •Scan configured sources for actionable signals
  • •Filter signals by recency, relevance, and action potential
  • •Map signals to action types (Thesis Candidate, Trigger Target, Partner Lead)
  • •Produce weekly signal digest with recommendations

Signal Sources

Configured Sources (from config/sources.yaml)

  1. •

    News & Media

    • •TechCrunch (Bitcoin, fintech, LATAM)
    • •CoinDesk (stablecoins, regulation, institutional adoption)
    • •The Block (funding rounds, partnerships)
    • •Bitcoin Magazine (ecosystem news)
  2. •

    Social & Community

    • •Bitcoin Twitter (key influencers, company announcements)
    • •LinkedIn (hiring, expansion, funding announcements)
    • •Reddit r/Bitcoin, r/bitcoinbeginners
  3. •

    Industry Sources

    • •LATAM fintech newsletters
    • •Mining industry publications
    • •Stablecoin integration announcements
  4. •

    Event & Conference Feeds

    • •Bitcoin conferences (speakers, sponsors)
    • •LATAM fintech events
    • •Mining conferences

Signal Filtering Rules

Recency Filter

  • •Signal must be <7 days old
  • •Exception: Funding rounds can be up to 60 days old
  • •Exception: Regulatory news can be up to 30 days old

Relevance Filter

Signal must relate to:

  • •Specific company or person (not generic industry trends)
  • •Identifiable buyer or decision maker
  • •Clear trigger or pain point
  • •Path to Growth OS segments (LATAM expansion, Bitcoin adoption, etc.)

Action Mapping

Each signal must map to exactly ONE action:

  • •Thesis Candidate: Suggests new targeting segment
  • •Trigger Target: Specific company with actionable trigger
  • •Partner Lead: Partnership opportunity
  • •Drop: Interesting but no clear action

Signal Digest Format

markdown
# Weekly Signal Digest — Week of [DATE]

## Summary
- Total signals scanned: [N]
- Actionable signals: [N]
- Top recommended action: [Thesis/Target/Partner]

---

## Thesis Candidates (Segment Opportunities)

| Signal | Source | Date | Proposed Segment |
|--------|--------|------|------------------|
| Brazil stablecoin regulation finalized | CoinDesk | 2026-01-22 | Brazil stablecoin adopters |
| ... | ... | ... | ... |

---

## Trigger Targets (Ready for Outreach)

| Company | Signal | Trigger Type | Source | Date | BU Fit |
|---------|--------|--------------|--------|------|--------|
| ACME Corp | Hiring LATAM contractors | Hiring | LinkedIn | 2026-01-25 | Bitwage |
| ... | ... | ... | ... | ... | ... |

---

## Partner Leads (Partnership Opportunities)

| Partner | Signal | Opportunity Type | Source | Date | Owner |
|---------|--------|------------------|--------|------|-------|
| Lightning Labs | Payment rail integration | Tech Partner | Twitter | 2026-01-23 | Christian |
| ... | ... | ... | ... | ... | ... |

---

## Dropped Signals (Interesting but No Action)

| Signal | Source | Reason Dropped |
|--------|--------|----------------|
| General BTC price movement | CoinDesk | No specific company/person |
| ... | ... | ... |

---

## Recommended Action

**Top Priority**: [Thesis Candidate / Trigger Target / Partner Lead]
**Reasoning**: [Why this signal has highest conversion potential]

Scope Guardrails

Apply these filters to maintain focus:

  1. •Signal Density: Segment must have ≥3 trigger-qualified companies
  2. •Buyer Clarity: Must identify specific buyer persona
  3. •Path to Pipeline: Clear conversion path (outreach → meeting → opportunity)

Signals that fail guardrails → "Dropped Signals" section

Integration with Other Modules

Feeds Into

  • •Module 2: Thesis Selector - Thesis candidate signals
  • •Module 3: Target Builder - Trigger target signals
  • •Module 7: Partner Brief - Partner lead signals

Data Sources

  • •config/sources.yaml - Source URLs and scan instructions
  • •knowledge/ecosystem-guide.md - Context for relevance filtering
  • •Previous week's thesis - Continuity context

Usage

When running Signal Scanner:

  1. •Provide the date range (typically last 7 days)
  2. •Include previous week's thesis for context
  3. •Specify any urgent signals to prioritize

The skill will:

  • •Scan all configured sources
  • •Apply filtering rules
  • •Generate action mapping
  • •Produce signal digest
  • •Highlight top recommended action

Example Workflow

code
Input: "Scan signals for week of 2026-01-29"

Process:
1. Scan news sources (TechCrunch, CoinDesk, etc.)
2. Scan social media (Twitter, LinkedIn)
3. Filter by recency (<7 days)
4. Filter by relevance (company/person specific)
5. Map to actions (Thesis/Target/Partner)
6. Apply scope guardrails
7. Generate digest with recommendations

Output: Signal digest markdown file

Signal Quality Scoring

Each actionable signal scores on:

  • •Trigger Strength (30%): How compelling is the trigger?
  • •Buyer Clarity (25%): Can we identify the buyer?
  • •Signal Freshness (20%): How recent is the signal?
  • •BU Fit (15%): How well does it fit our BUs?
  • •Conversion History (10%): Have similar signals converted?

Signals scoring >70% are prioritized.

Configuration

Located in: config/sources.yaml

yaml
sources:
  - name: TechCrunch
    url: https://techcrunch.com/
    categories: [bitcoin, fintech, latam]
    scan_frequency: daily
    relevance_keywords:
      - funding
      - expansion
      - latam
      - bitcoin
      - stablecoin

  - name: Bitcoin Twitter
    type: manual_review
    accounts:
      - @Bitcoin
      - @aantonop
      - @saifedean
    scan_frequency: daily

  # ... more sources

Notes

  • •Uses native WebFetch and WebSearch tools
  • •Can integrate with Firecrawl skill for structured scraping
  • •Twitter/X scanning remains manual (no reliable API)
  • •Signals are never auto-converted to targets without human approval