Prepare for customer meetings with a concise brief built from Common Room data. Combine company activity, attendee profiles, and previous conversations into specific talking points, likely discussion topics, and a recommended meeting outcome.
中文简介正在准备中。当前显示英语简介。
Prepare for a customer or prospect call using Common Room signals. Triggers on 'prep me for my call with [company]', 'prepare for a meeting with [company]', 'what should I know before talking to [company]', or any call preparation request.
安装前可以查看交给 AI 代理的指令内容。
Produce a complete, scannable call prep brief by combining account research, contact research, and signal synthesis from Common Room.
Parse what the user has provided:
Calendar lookup: If a ~~calendar connector is available, search for upcoming meetings with the named company to automatically surface attendee names, meeting time, and any meeting notes or agenda. Use this to fill gaps the user didn't provide.
If neither attendees nor a calendar match can be found, ask: "Who will be on the call from [Company]? I can research each attendee to make your prep more useful."
Use the account-research skill process to build a full account snapshot. For call prep, prioritize:
When reviewing activity history, prioritize Gong and call recording activities — these provide direct context about previous conversations. Do not filter out call recordings by activity origin.
For each external attendee, use the contact-research skill process. For call prep, focus on:
Based on the combined account and contact research:
When the user's company context is available (see references/my-company-context.md), tailor talking points to the user's product and value proposition.
After gathering all Common Room data, run a quick recency check to catch anything that happened since the last CR data sync. This is supplementary — CR data drives the prep; web search only adds recency.
Company news: Search "[company name]" news filtered to the last 14 days. Look for funding announcements, product launches, leadership changes, layoffs, partnerships, or press coverage.
Attendee presence: For each external attendee, search "[full name]" "[company name]" — look for recent articles, LinkedIn posts, conference talks, podcasts, or published opinions.
If a company news item is significant (e.g., just raised a round, announced a major hire), flag it in Signal Highlights. Otherwise, include findings briefly — don't let web search results overshadow CR signals.
The output adapts to how much data Common Room returned. Only include sections where you have real data. Never fill a section with invented details.
## Call Prep: [Company] — [Date/Time if known]
**Meeting Context**
[Attendees, meeting type, and any known agenda]
---
### Company Snapshot
[4–6 bullets: key account status, signals, and recent activity]
---
### Attendee Profiles
**[Attendee Name] — [Title]**
[3–4 bullets: role, recent activity, Spark persona if available, personal hook]
[Repeat for each attendee]
---
### Signal Highlights
[Top 3 signals most relevant to this specific call]
---
### Talking Points
1. [Point tied to a specific signal]
2. [Point tied to a specific signal]
3. [Point tied to a specific signal]
### Likely Topics / Objections to Prepare For
- [Topic or objection + suggested response]
- [Topic or objection + suggested response]
### Recommended Call Outcome
[1–2 sentences: what success looks like for this meeting]
## Call Prep: [Company] — [Date/Time if known]
**Data available:** [List exactly what Common Room returned — e.g., "Name, title, email, two tags. No activity history, no scores, no Spark data."]
### What I Found
[Only the fields actually returned, presented as-is]
### Web Search Results
[Findings from web search on the company and attendees — or "No significant results"]
### Suggested Next Steps
- I can pull [specific field groups] from Common Room if available
- I can run deeper web searches on [specific topics]
- You may want to check Common Room directly for [what's missing]
Do not generate a full call prep brief from sparse data. A short honest output is always better than a long fabricated one.
references/call-types-guide.md — guidance for different call types (discovery, expansion, renewal, QBR) and how to tailor prep accordingly还没有评价。欢迎分享你的使用感受。
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Review a design or web page against WCAG 2.1 AA, an accessibility standard. Organize findings on contrast, keyboard access, forms, and screen reader behavior, with severity levels and practical recommendations for fixes.
中文简介正在准备中。当前显示英语简介。
Build a single brief on an existing customer using available sales records, emails, documents, call notes, and internal chat. Understand the current situation, key contacts, recent discussions, and gaps that may need attention.
中文简介正在准备中。当前显示英语简介。
Build or refresh a strategic customer account plan from sales records, emails, and meeting transcripts. Organize goals, stakeholders, growth opportunities, risks, and dated actions into a document, then sync approved highlights to the customer relationship management system.
中文简介正在准备中。当前显示英语简介。
Research sales accounts using Common Room data to summarize company details, buying signals, ownership, and key contacts. Answer specific questions directly or prepare a broader briefing with evidence-based next steps, clearly identifying missing information.
中文简介正在准备中。当前显示英语简介。
Research prospective companies and contacts, check existing customer records, and assess fit against your ideal customer profile. Receive a sourced brief covering recent developments, likely priorities, outreach talking points, and a suggested next step.
中文简介正在准备中。当前显示英语简介。
Score and group accounts by customer fit and engagement, such as recent contact and open sales opportunities. Identify where to focus sales effort, choose next actions, and spot promising accounts with neglected outreach or missing information.
中文简介正在准备中。当前显示英语简介。