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 objection-blocker-trackergit 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/objection-blocker-tracker)<a href="https://agentmods.dev/skills/zoominfo/zoominfo-mcp-plugin/objection-blocker-tracker"><img src="https://agentmods.dev/badge/skills/zoominfo/zoominfo-mcp-plugin/objection-blocker-tracker/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/objection-blocker-tracker"><img src="https://agentmods.dev/badge/skills/zoominfo/zoominfo-mcp-plugin/objection-blocker-tracker.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 | $0.00120 | $0.00648 |
| Opus 5 | $0.00060 | $0.00324 |
| Sonnet 5 | $0.00024 | $0.00130 |
| Haiku 4.5 | $0.00012 | $0.00065 |
Grade A, and why
objection-blocker-tracker 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 9d 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Objection & Blocker Tracker
Surface the concerns standing between you and the deal, and show whether each is getting better or worse.
Prerequisites
conversation_intelligence requires at least one connected meeting or email source and consumes AI credits. browse_engagements (to scope or pick calls) requires an active integration and is free. If no conversation data exists, say so rather than reporting "no objections" (the absence of data is not the absence of objections).
Input
Provided via $ARGUMENTS:
- Scope (required) — an account or contact (ZoomInfo ID, or a name to resolve).
- Focus (optional) — e.g. "just pricing", "anything technical", "security and procurement". Narrows the read.
Workflow
- Resolve scope. If no account or contact was supplied, ask the user which one before proceeding. Use a ZoomInfo ID directly, or resolve a name via
search_companies/search_contacts. - Extract objections and blockers. Run
conversation_intelligencescoped to the account or contact. Ask it to list the objections, concerns, and blockers raised across recent conversations, who raised each, when, and how it was last left. Keep CI scoped to one ID; it sees only the last few engagements and cannot count or topic-search, so present this as recent movement, not a complete tally. - Track the trajectory. For each item, classify status: newly raised, addressed/resolved, recurring (keeps coming back), or escalating. Tie each to the source moments. Do not record an objection the conversation does not support, and do not mark something resolved without evidence it was.
Output Format
Open objections & blockers — [Account / Contact]
From the last few engagements (through [date]).
For each, most pressing first:
[Objection / blocker] — [status: new | recurring | escalating | addressed]
- Raised by: [who, when]
- Evolution: how it has moved across calls (e.g. "raised in discovery, partially addressed in the demo, resurfaced on the last call").
- Where it stands: the current state and what would move it.
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.
- 9d ago First seen · 45 lines · 120 tokens per session scan A e8c749727a67
objection-blocker-tracker is a skill published in the GitHub repository Zoominfo/zoominfo-mcp-plugin (7 stars, last pushed 5d ago), licensed MIT. It adds 120 tokens to every session and 648 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…