signal-detection-pipeline
Detect buying signals from multiple sources, qualify leads, and generate outreach context
Best use case
signal-detection-pipeline is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Detect buying signals from multiple sources, qualify leads, and generate outreach context
Teams using signal-detection-pipeline 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/signal-detection-pipeline/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How signal-detection-pipeline Compares
| Feature / Agent | signal-detection-pipeline | 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?
Detect buying signals from multiple sources, qualify leads, and generate outreach context
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
# Signal Detection Pipeline Monitor multiple signal sources to find companies actively in-market for your client's solution. Combine signals for higher-confidence leads. ## When to Use - "Find companies that might need [our product]" - "Run signal detection for [problem area]" - "Find buying signals in [industry/topic]" ## Signal Sources Run the sources relevant to the client's ICP. Each is independent — run in parallel. ### Job Posting Signals (Strongest) **Skill:** job-posting-intent Companies hiring for roles in the problem area = budget allocated and pain acknowledged. - Input: Job keywords, ICP criteria - Output: Qualified companies with outreach angles ### Funding Signals **Skill:** funding-signal-monitor Recently funded companies = budget available, growth mandate. - Input: Industry, funding stage filter - Output: Funded companies with timing context ### Conference Attendance Signals **Skill:** luma-event-attendees People attending events in the problem space = actively engaged. - Input: Event URLs or topic search - Output: Person/company list ### Reddit Pain Signals **Skill:** reddit-scraper People complaining about or discussing the problem = experiencing the pain. - Input: Keywords, relevant subreddits - Output: Posts with authors, context ### LinkedIn Content Signals **Skill:** linkedin-post-research + linkedin-commenter-extractor People posting about or engaging with the problem = thought leaders or practitioners. - Input: Keywords, time frame - Output: Posters and commenters with engagement data ## Combining Signals After running relevant sources: 1. **Deduplicate** companies appearing across multiple signals (multi-signal = strongest leads) 2. **Score** each lead: assign signal strength based on source quality and recency - Job posting + funding = highest intent - LinkedIn post + Reddit complaint = validated pain - Single conference attendance = lowest (awareness only) 3. **Enrich** top leads with web search for company details 4. **Consolidate** into a single Google Sheet: Company, Signal Sources, Signal Strength, Context, Outreach Angle 5. **Prioritize** companies with multiple signal types ## Human Checkpoints - **After combining signals**: Review consolidated list before outreach
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