Rank a list of accounts (mixed Explorium business IDs, company names, or domains) by ICP fit, buying intent, recent triggers, and workforce momentum. Returns per-account composite score (0-100), tier (A/B/C), explainable component breakdown (fit / intent / trigger / workforce), and a specific "why now" sentence per account anchored on a real Explorium signal. Resolves name/domain inputs via match-business with explicit confirmation for ambiguous matches. Iteratively refinable. Use for account-based selling, ABM list prioritization, territory planning, signal-based selling, buyer-intent ranking, and B2B prospecting. Triggers on "score these accounts", "rank by ICP fit and intent", "prioritize this account list", "which accounts should I work first", "build a tiered account list", "ICP scoring", "account prioritization".
Drop this skill into Claude Code and your AI agent gains the ability to score and tier a list of accounts on four axes by fetching firmographics, technographics, intent, events, and workforce trends from explorium, then applying a transparent weighted composite the calling model computes from the returned data.
This skill is part of a 14-skill series covering the full B2B sales workflow, powered by the Explorium AgentSource API — 350M+ people, 80M+ companies, real-time firmographics, technographics, funding signals, and verified contact data.
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├── SKILL.md # Full skill definition — input, workflow, output format, limitations
├── llms.txt # AI-readable summary of this skill and the full series
└── README.md
/plugin marketplace add https://github.com/explorium-ai/Agent-skills
Point your agent at SKILL.md for the full skill instructions.
Invoke with your target account or dataset.
MIT