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 next-best-actiongit 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/next-best-action)<a href="https://agentmods.dev/skills/zoominfo/zoominfo-mcp-plugin/next-best-action"><img src="https://agentmods.dev/badge/skills/zoominfo/zoominfo-mcp-plugin/next-best-action/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/next-best-action"><img src="https://agentmods.dev/badge/skills/zoominfo/zoominfo-mcp-plugin/next-best-action.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00118 | $0.00673 |
| Opus 5 | $0.00059 | $0.00336 |
| Sonnet 5 | $0.00024 | $0.00135 |
| Haiku 4.5 | $0.00012 | $0.00067 |
Grade A, and why
next-best-action 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 13d 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 — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Next-Best-Action
Read the current state of the conversation and recommend the one or two moves most likely to advance it.
Prerequisites
conversation_intelligence requires at least one connected email or meeting source; conversation_intelligence and account_research consume AI credits. If no conversation data exists, base the recommendation on account_research and say the read is limited, pointing the user to their ZoomInfo admin.
Input
Provided via $ARGUMENTS:
- Scope (required) — an account, a contact, or a specific engagement (ID, or a name to resolve).
- Goal (optional) — e.g. "get to a technical eval", "close this quarter", "re-engage a stalled deal". Sharpens the recommendation.
Workflow
- Resolve scope. Use a ZoomInfo ID directly, or resolve via
search_companies/search_contactsand confirm an ambiguous match before spending credits (conversation_intelligenceandaccount_researchboth cost AI credits, so a wrong resolution burns them). For a specific call not named, offer abrowse_engagementsshortlist first. - Read the state. Run
conversation_intelligencescoped to the account/contact/engagement for where things stand: open threads, stated next steps, blockers, buying signals, and unanswered questions. Pullaccount_researchfor deal stage and stakeholder context. Keep CI scoped to one ID; it sees only the last few engagements and cannot search by topic or count, so reason from what it returns. - Recommend. Propose one to three concrete next actions, ranked, each tied to specific evidence from the conversations and aimed at the stated goal. For each, give the move, why now (the evidence), and the expected effect. Skip generic advice — if the evidence does not support a confident recommendation, say what is missing and what to find out next instead.
Output Format
Next best action — [Account / Contact]
State of play — 2-3 lines on where things stand right now, from the conversations.
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.
- 13d ago First seen · 41 lines · 118 tokens per session scan A 65154a1eb644
next-best-action is a skill published in the GitHub repository Zoominfo/zoominfo-mcp-plugin (7 stars, last pushed 8d ago), licensed MIT. It adds 118 tokens to every session and 673 once invoked, about $0.0006 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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