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 call-recapgit 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/call-recap)<a href="https://agentmods.dev/skills/zoominfo/zoominfo-mcp-plugin/call-recap"><img src="https://agentmods.dev/badge/skills/zoominfo/zoominfo-mcp-plugin/call-recap/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/call-recap"><img src="https://agentmods.dev/badge/skills/zoominfo/zoominfo-mcp-plugin/call-recap.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 | $0.00130 | $0.00962 |
| Opus 5 | $0.00065 | $0.00481 |
| Sonnet 5 | $0.00026 | $0.00192 |
| Haiku 4.5 | $0.00013 | $0.00096 |
Grade A, and why
call-recap 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Call Recap
Turn a just-finished call into a compact, high-signal recap: what was discussed, what was decided, who owns what, and what is still open.
Prerequisites
browse_engagements (to find the call) requires an active calendar/email/meeting integration. conversation_intelligence (to read the call) requires at least one connected meeting or email source. Both conversation_intelligence and account_research consume AI credits. If no conversation data is available for the call, say so and point the user to their ZoomInfo admin rather than guessing at content.
Input
Provided via $ARGUMENTS:
- Which call (optional) — an account and/or a date ("the Acme call", "yesterday's demo"). If omitted, the skill lists recent calls to pick from.
- Emphasis (optional) — e.g. "just the action items", "what did we decide", "for my manager". Shapes the output.
Workflow
-
Identify the call.
- If the user named an account or date, resolve the account via
search_companiesfirst if needed (browse_engagementsfilters by company/contact ID and date, not by call name), then callbrowse_engagements(engagementType: MEETINGS,sort: -chronological) scoped to that ID and date window and confirm the match. - If nothing was named, call
browse_engagementsfor the user's recent meetings and present a numbered shortlist (date, title, account, participants). Let the user pick one (or several) before spending AI credits. Keep each chosen engagement's ID.
- If the user named an account or date, resolve the account via
-
Read the call with
conversation_intelligence. Scope CI to the chosen engagement ID and ask for a structured read: what was discussed, decisions made, action items with owners and any stated due dates, open questions, and notable customer statements. For multiple selected calls, run one CI call per engagement (do not ask one CI call to span several). Keep the query specific to that engagement; CI cannot search by topic or count mentions. -
Add light context (optional). If deal/relationship framing helps, pull
account_researchfor the account — kept brief. Skip it if the user just wants the recap itself; this is a recap, not a full account brief.
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 · 60 lines · 130 tokens per session scan A 4896b91bc2cd
call-recap is a skill published in the GitHub repository Zoominfo/zoominfo-mcp-plugin (7 stars, last pushed 7d ago), licensed MIT. It adds 130 tokens to every session and 962 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
recipe-create-meet-space
Create a Google Meet meeting space and share the join link.
workthreads
SpecStory Workthreads - a weekly work-thread rollup across a team's repos from SpecStory coding histories (any agent - Claude Code, Codex, Cursor, Gemini, and more). It groups the window's sessions into threads of work per project and labels each new / open / recently closed, so a lead sees what shipped, what is still…
atmos-config
Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.
story-readiness
Validate that a story file is implementation-ready. Checks for embedded GDD requirements, ADR references, engine notes, clear acceptance criteria, and no open design questions. Produces READY / NEEDS WORK / BLOCKED verdict with specific gaps. Use when user says 'is this story ready', 'can I start on this story', 'is…
autotask-creator
Rules for automation CRUD from the group-chat commander. The commander does not call mutation tools and does not edit cloud/autotasks files directly. It emits one or more top-level ... containers in its final text; the bus parses and applies them after the turn.
remove
Remove a deployed framework or addon from the current workspace.