score-leads

score-leads is a skill for Claude Code from Zoominfo/zoominfo-mcp-plugin. It costs 177 tokens per session (4,848 once invoked), scanned A, original, MIT.

A lead-ranking tool that sorts potential customers or cold contacts into Hot, Warm, or Cold tiers and gives each one a response-time target. It also explains the main reason for each ranking.

In plain words
What is it for?
Use it to order an SDR calling queue, route new inbound leads, triage marketing-qualified or product-qualified leads, and prioritize event or content follow-up.
Why use it?
It removes guesswork from deciding which people to contact first. It also helps prevent missed follow-ups, bad contact matches, and vague outreach instructions.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the zoominfo plugin — 35 skills, 1 MCP server shipped together

Good fit Use it to order an SDR calling queue, route new inbound leads, triage marketing-qualified or product-qualified leads, and prioritize event or content follow-up.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zoominfo/zoominfo-mcp-plugin/score-leads
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Zoominfo/zoominfo-mcp-plugin --skill score-leads
Clone the repo
git clone --depth 1 https://github.com/Zoominfo/zoominfo-mcp-plugin

Made for: Claude Code.

Or install zoominfo, the plugin that ships this one along with the rest of its 35 skills, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for score-leads

README.md
[![agentmods](https://agentmods.dev/badge/skills/zoominfo/zoominfo-mcp-plugin/score-leads/github.svg)](https://agentmods.dev/skills/zoominfo/zoominfo-mcp-plugin/score-leads)
Your own site
<a href="https://agentmods.dev/skills/zoominfo/zoominfo-mcp-plugin/score-leads"><img src="https://agentmods.dev/badge/skills/zoominfo/zoominfo-mcp-plugin/score-leads/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for score-leads

Your own site · 80×15
<a href="https://agentmods.dev/skills/zoominfo/zoominfo-mcp-plugin/score-leads"><img src="https://agentmods.dev/badge/skills/zoominfo/zoominfo-mcp-plugin/score-leads.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 177 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,848 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00177 $0.04848
Opus 5 $0.00088 $0.02424
Sonnet 5 $0.00035 $0.00970
Haiku 4.5 $0.00018 $0.00485

Measured 11d ago against content hash 70796a2a1cc0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

score-leads scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/score-leads/SKILL.md · 316 lines

How it starts

The opening of the file, as written. The whole thing — 316 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Score Leads

Tier leads as Hot / Warm / Cold with a response-time SLA tuned to the use case. Calls get_gtm_context(detailed: true) unconditionally, resolves leads by email (deterministic) or name+company (surface ambiguity), scores on four axes, and presents a scannable per-lead output with a specific "why now" reasoning snippet so the rep can trust the tier.

The bar

  1. Tier and SLA are the first thing the rep sees — not buried under TL;DR or component breakdown.
  2. Resolution accuracy 100% — every input bucketed; email typos fail loudly, never silent fallback to name search.
  3. Every Hot lead carries verified contact data — phone + accuracy score visible. Bad data on a Hot lead = dial-the-wrong-number failure.
  4. Every tier comes with a concrete next action — "Direct dial 555-1234. Lead with [signal]." Not "engage promptly."
  5. Every lead carries a "why now" reasoning snippet — citing the specific axis driver (person seat × source × fresh trigger / intent / prior engagement). Never the composite restated; never generic ("strong fit"). Same trust discipline as score-accounts.
  6. Output scannable in <30 seconds per row. Component breakdown below the fold.

Scope

Scores individual leads, not accounts. Use score-accounts for company-level prioritization. For Hot leads, chain to personalize-email.

Input

  • Leads (required) — list of ZI person IDs / emails / name+company rows / mixed CSV.
  • Source (recommended)demo_request, pricing_inquiry, free_trial, product_signup, content_download_high_intent, content_download_low_intent, webinar_attended, webinar_registered, newsletter_subscribe, cold_inbound, unknown. If missing, ask once then default to unknown (source = 50, flagged).
  • Use case (default inbound_routing)inbound_routing, event_followup, pql_triage, content_follow_up. Drives SLA tuning.
  • Weight overrides (optional){person, account, source, trigger} summing to 100.
  • Tier thresholds (optional){Hot, Warm}. Cold is the remainder.

Read the full file on GitHub · 316 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 316 lines · 177 tokens per session scan A 70796a2a1cc0

Subscribe to this mod's changes

score-leads is a skill published in the GitHub repository Zoominfo/zoominfo-mcp-plugin (7 stars, last pushed 7d ago), licensed MIT. It adds 177 tokens to every session and 4,848 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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