AgentSkillsCN

signal-intent-scoring

在分析原始潜在客户数据或职位招聘信息时，此工具可帮助您评估其“营收影响”潜力。依据 Basin::Nexus 信号精炼框架，对目标企业进行评分与筛选。

SKILL.md
--- frontmatter
name: signal-intent-scoring
description: "Use when analyzing raw lead data or job postings to determine the 'Revenue Impact' potential. Scores targets based on the Basin::Nexus Signal Refinery framework."

Signal Intent Scoring

Overview

Automate the qualification of "Strategic Targets" by grading deep signal triggers. This replaces manual "vibe checks" with an engineered scoring system.

The Process

1. Data Ingestion

  • •Extract headcount trends from LinkedIn/Crunchbase.
  • •Note funding rounds (Series A/B is the sweet spot).
  • •Identify "Deviance Triggers" from job descriptions:
    • •High volume of "Founding SDR" roles = High Latency signal.
    • •Mentions of "Manual CRM entry" = Broken Pipe signal.
    • •"Starting the GTM from scratch" = Vacuum signal.

2. Scoring Algorithm (0-100)

  • •Base Score (40): Series A/B Funding.
  • •Complexity Multiplier (+20): Shifting from PLG to Enterprise sales.
  • •Friction Bonus (+30): High hiring volume for manual roles (SDR/BDR).
  • •Architecture Penalty (-20): 500+ headcount (Too much bureaucratic friction).

3. Verdict Generation

Output a "Lead Status Brief":

  • •Grade: e.g., "92/100 (HIGH SIGNAL)".
  • •Diagnosis: e.g., "Target is launching missions with erring O-rings (manual prospecting for an AI product)."
  • •Strike Angle: Identify the specific Basin::Nexus module to pitch (e.g., "Signal Refinery").

Key Principles

  • •Score the Problem, Not the Product: Focus on their operational failure.
  • •Temporal Discounting: Leads decay. Prioritize "Fresh" signals over "Stale" ones.
  • •Bias for Engineering: Favor targets where a Python script can replace 3 humans.