Signal Detection Pipeline
Detect buying signals from multiple sources, qualify leads, and generate outreach context. This runbook orchestrates multiple independent signal-detection sub-skills (job postings, funding events, conference attendance, Reddit discussions, and LinkedIn content) to surface compani
9 steps · start to finish.
- 1Step 1
Environment Setup
▶pip install requests pyyaml pandas mkdir -p /app/results # Validate required inputs if [ -z "$TARGET_KEYWORDS" ]; then echo "ERROR: TARGET_KEYWORDS is not set"; exit 1 fi if [ -z "$ICP_CRITERIA" ]; then echo "ERROR: ICP_CRITERIA is not set"; exit 1 fi echo "Environment ready — Keywords: $TARGET_KEYWORDS | ICP: $ICP_CRITERIA" - 2Step 2
Run Signal Sources in Parallel
▶Run the sources relevant to the client's ICP. Each is independent — run in parallel.
- 3Step 3
Combine and Deduplicate Signals
▶After all sources complete, merge and deduplicate:
- 4Step 4
Score and Qualify Leads
▶Apply `lead-qualification` skill to the deduplicated list:
- 5Step 5
Human Checkpoint — Review Before Proceeding
▶**STOP HERE** — review the consolidated lead list before initiating outreach.
- 6Step 6
Iterate on Errors (max 3 rounds)
▶If any signal source returned zero leads or an error:
- 7Step 7
Check Contact Cache
▶Deduplicate final leads against previously contacted companies:
- 8Step 8
Write Executive Summary
▶import pandas as pd, pathlib df = pd.read_csv("/app/results/qualified_leads.csv") summary = f"""# Signal Detection Pipeline — Results
- 9Step 9
Final Checklist (MANDATORY — do not skip)
▶echo "=== FINAL OUTPUT VERIFICATION ===" RESULTS_DIR="/app/results" for f in \ "$RESULTS_DIR/qualified_leads.csv" \