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 decision-process-mappergit 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/decision-process-mapper)<a href="https://agentmods.dev/skills/zoominfo/zoominfo-mcp-plugin/decision-process-mapper"><img src="https://agentmods.dev/badge/skills/zoominfo/zoominfo-mcp-plugin/decision-process-mapper.svg" alt="Measured on agentmods" 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 | $0.00129 | $0.00645 |
| Opus 5 | $0.00064 | $0.00322 |
| Sonnet 5 | $0.00026 | $0.00129 |
| Haiku 4.5 | $0.00013 | $0.00064 |
Grade A, and why
decision-process-mapper 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 8d 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 — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Decision-Process Mapper
Reconstruct how the prospect actually buys, from what they have told you: criteria, steps, timeline, and the people who decide.
Prerequisites
conversation_intelligence requires at least one connected meeting or email source; conversation_intelligence and account_research consume AI credits. If no conversation data exists, build what you can from account_research and mark the rest unknown, pointing the user to their ZoomInfo admin.
Input
Provided via $ARGUMENTS:
- Account (required) — ZoomInfo company ID (preferred), or a name/domain to resolve via
search_companies. - Framework (optional) — e.g. "MEDDIC", "just the approvers and timeline". Shapes which fields to foreground.
Workflow
- Resolve the account. Use the ZoomInfo ID directly, or resolve a name/domain via
search_companies. - Extract the process. Run
conversation_intelligencescoped to the account, asking what the prospect has said about how they will decide: the decision criteria, the evaluation steps, the timeline and any deadlines, the budget or procurement process, and who is involved in or approves the decision. Runaccount_researchfor the org/stakeholder picture. Keep CI scoped to one account; it sees only the last few engagements and cannot topic-search, so map what was said, not the whole sales cycle. - Map, and mark gaps honestly. Assemble the process. For anything not actually stated in conversation, label it not stated rather than inferring it. Distinguish a named approver from a guessed one. Tie each filled field to the source moment.
Output Format
Decision process — [Company]
| Element | What they said | Source / status |
|---|---|---|
| Decision criteria | ||
| Evaluation steps | ||
| Timeline / deadline | ||
| Budget / procurement | ||
| Decision-makers & approvers | ||
| Champion |
Use not stated in any cell the conversations did not cover.
Biggest gaps — the two or three unknowns that most need confirming, and a question to surface each on the next call.
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.
- 8d ago First seen · 47 lines · 129 tokens per session scan A d4345403666c
decision-process-mapper is a skill published in the GitHub repository Zoominfo/zoominfo-mcp-plugin (7 stars, last pushed 4d ago), licensed MIT. It adds 129 tokens to every session and 645 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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