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Call Prep

  • 2.2k installs
  • 23.1k repo stars
  • Updated July 28, 2026
  • anthropics/knowledge-work-plugins

call-prep is an agent skill that Prepare for a customer or prospect call using Common Room signals. Triggers on 'prep me for my call with [company]', 'pr.

About

Produce a complete scannable call prep brief by combining account research contact research and signal synthesis from Common Room Step 1 Identify the Account and Attendees Parse what the user has provided Company name required look up the account in Common Room Attendee names optional if provided research each one 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 The call prep agent skill provides documented workflows prerequisites triggers and safety guidance from its SKILL md source Agents load it when user requests match the description and follow step by step instructions without inventing capabilities It integrates with standard agent tooling for the tasks inputs outputs and failure modes described

  • description: "Prepare for a customer or prospect call using Common Room signals. Triggers on 'prep me for my call with [
  • Produce a complete, scannable call prep brief by combining account research, contact research, and signal synthesis from
  • - **Company name** — required; look up the account in Common Room
  • Follow call-prep SKILL.md steps and documented constraints.
  • Follow call-prep SKILL.md steps and documented constraints.

Call Prep by the numbers

  • 2,249 all-time installs (skills.sh)
  • +91 installs in the week ending Jul 28, 2026 (Skillselion tracking)
  • Ranked #399 of 16,659 AI & Agent Building skills by installs in the Skillselion catalog
  • Security screen: MEDIUM risk (skills.sh audit)
  • Data as of Jul 28, 2026 (Skillselion catalog sync)
At a glance

call-prep capabilities & compatibility

Capabilities
description: "prepare for a customer or prospect · produce a complete, scannable call prep brief by · **company name** — required; look up the accou · follow call prep skill.md steps and documented c
Use cases
orchestration
From the docs

What call-prep says it does

description: "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 ta
SKILL.md
Produce a complete, scannable call prep brief by combining account research, contact research, and signal synthesis from Common Room.
SKILL.md
- **Company name** — required; look up the account in Common Room
SKILL.md
npx skills add https://github.com/anthropics/knowledge-work-plugins --skill call-prep

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Listed on Skillselion
Installs2.2k
repo stars23.1k
Security audit2 / 3 scanners passed
Last updatedJuly 28, 2026
Repositoryanthropics/knowledge-work-plugins

When should an agent use call-prep and what problem does it solve?

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 [comp

Who is it for?

Developers invoking call-prep as documented in the skill source.

Skip if: Skip when requirements fall outside call-prep documented scope.

When should I use this skill?

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 [comp

What you get

Outputs aligned with the call-prep SKILL.md workflow and stated deliverables.

  • call briefing
  • question list
  • meeting agenda

Files

SKILL.mdMarkdownGitHub ↗

Call Prep

Produce a complete, scannable call prep brief by combining account research, contact research, and signal synthesis from Common Room.

Prep Process

Step 1: Identify the Account and Attendees

Parse what the user has provided:

  • Company name — required; look up the account in Common Room
  • Attendee names — optional; if provided, research each one

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."

Step 2: Run Account Research

Use the account-research skill process to build a full account snapshot. For call prep, prioritize:

  • Recent product signals (what are they doing in the product right now?)
  • Open opportunities or renewal timeline
  • Any risk signals (declining usage, support tickets, churned seats)
  • Key recent events (funding, executive change, new hire)

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.

Step 3: Run Contact Research for Each Attendee

For each external attendee, use the contact-research skill process. For call prep, focus on:

  • Role and influence in the buying process
  • Their personal activity and engagement history
  • Any recent signals that suggest their current mood/priorities
  • Spark persona classification if available

Step 4: Synthesize Talking Points and Objectives

Based on the combined account and contact research:

  • Identify the call objective (e.g., discovery, demo, expansion conversation, renewal, QBR)
  • Generate 3–5 tailored talking points grounded in specific signal data
  • Anticipate 2–3 likely objections or topics the customer may raise
  • Suggest a recommended outcome for the call

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.

Step 5: Recency Check (Web Search)

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.

Output Format

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.

When data is rich (multiple field groups returned, activity history, scores, signals):

## 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]

When data is sparse (few fields returned, no activity, null sparkSummary):

## 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.

Quality Standards

  • Ground every talking point in a real signal — no generic filler
  • Keep the brief tight — it should be readable in 5 minutes or less
  • Flag unknowns explicitly — if attendee research is thin, say so
  • Time-box the research — don't over-research at the expense of speed
  • Never invent deal context — no fabricated proposals, competitor comparisons, pricing, trial terms, or objections not returned by a tool call

Reference Files

  • `references/call-types-guide.md` — guidance for different call types (discovery, expansion, renewal, QBR) and how to tailor prep accordingly

Related skills

FAQ

What is call-prep?

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 bef

When should I use call-prep?

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 bef

Is call-prep safe to install?

Review the Security Audits panel on this page before production use.

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