apps/api/app/skills/ai_lead_rubric/SKILL.md
--- name: AI Lead Scoring engine: markdown version: 1 category: sales tags: [leads, scoring, AI, qualification, BANT] auto_trigger: "Score leads for AI platform fit using the AI Lead Scoring rubric" inputs: - name: entity_id type: string description: "Knowledge entity UUID to score" required: true --- ## Description Score leads 0-100 based on likelihood of becoming a customer for an AI/agent orchestration platform. ## Scoring Rubric (0-100 total) | Category | Max Points | What
npx skillsauth add nomad3/servicetsunami-agents AI Lead ScoringInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Score leads 0-100 based on likelihood of becoming a customer for an AI/agent orchestration platform.
| Category | Max Points | What to look for | |---|---|---| | hiring | 25 | Job posts mentioning AI, ML, agents, orchestration, automation, platform engineering | | tech_stack | 20 | Uses or evaluates LangChain, OpenAI, Anthropic, CrewAI, AutoGen, or similar agent frameworks | | funding | 20 | Recent funding round (Series A/B/C within 12 months scores highest) | | company_size | 15 | Mid-market (50-500 employees) and growth-stage companies score highest | | news | 10 | Recent product launches, partnerships, expansions, AI initiatives | | direct_fit | 10 | Explicit mentions of orchestration needs, multi-agent workflows, workflow automation |
{relations_text}
Return ONLY a JSON object with this exact structure:
{
"score": "<integer 0-100>",
"breakdown": {
"hiring": "<integer 0-25>",
"tech_stack": "<integer 0-20>",
"funding": "<integer 0-20>",
"company_size": "<integer 0-15>",
"news": "<integer 0-10>",
"direct_fit": "<integer 0-10>"
},
"reasoning": "<one paragraph explaining the score>"
}
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