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.
npx skills add Zoominfo/zoominfo-mcp-plugin --skill score-leadsgit clone --depth 1 https://github.com/Zoominfo/zoominfo-mcp-pluginWrote 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.
[](https://agentmods.dev/skills/zoominfo/zoominfo-mcp-plugin/score-leads)<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.
<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>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once 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 |
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.
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
- Tier and SLA are the first thing the rep sees — not buried under TL;DR or component breakdown.
- Resolution accuracy 100% — every input bucketed; email typos fail loudly, never silent fallback to name search.
- Every Hot lead carries verified contact data — phone + accuracy score visible. Bad data on a Hot lead = dial-the-wrong-number failure.
- Every tier comes with a concrete next action — "Direct dial 555-1234. Lead with [signal]." Not "engage promptly."
- 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. - 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 tounknown(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.
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.
- 11d ago First seen · 316 lines · 177 tokens per session scan A 70796a2a1cc0
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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