# Meeting Prep > Generates a one-page meeting prep brief before any sales or customer call. Pulls from HubSpot, Fireflies, and Apollo, cross-references data across sources, and delivers a structured brief with company context, relationship history, deal status, past meeting highlights, and recommended talking points. Use this skill when the user says "prep for my meeting with...", "meeting prep", "get ready for my call with...", "prep me for [company]", "what do I need to know before my call with...", or "brief me on [company/person]". - Skill: `jp-solumhealth/meeting-prep` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add jp-solumhealth/meeting-prep` - Raw SKILL.md: https://api.skillmd.com/api/skills/jp-solumhealth/meeting-prep/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Productivity - Author: jp-solumhealth (https://skillmd.com/u/jp-solumhealth) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/jp-solumhealth/meeting-prep --- # Meeting Prep — Pre-Call Intelligence Brief Your job is to build a comprehensive, cross-referenced meeting prep brief before JP gets on a sales or customer call. Pull from every available data source, verify data consistency across sources, and deliver a structured brief that makes JP the most prepared person on the call. ## Trigger Patterns Activate this skill when the user says any of the following: - "prep for my meeting with [company/person]" - "meeting prep [company/person]" - "get ready for my call with [company/person]" - "prep me for [company/person]" - "what do I need to know before my call with [company/person]" - "brief me on [company/person]" - "prep [company/person]" - "call prep [company/person]" ## Input Parsing Extract the following from the user's request: - **Company name** (required) — the organization being met with - **Person name** (optional) — specific contact(s) at the company - **Meeting date/time** (optional) — when the meeting is scheduled If only a person name is given, use HubSpot and Apollo to resolve their company. If ambiguous, ask the user to clarify before proceeding. ## Data Collection Workflow ### Step 1: Resolve Identifiers Start by finding the company and contact in HubSpot so you have IDs for subsequent queries. ``` Call: mcp__claude_ai_HubSpot__search_crm_objects Params: objectType: "companies" filterGroups: [ { filters: [ { propertyName: "name", operator: "CONTAINS_TOKEN", value: "" } ]} ] properties: ["name", "domain", "industry", "numberofemployees", "city", "state", "country", "phone", "description", "hs_lastmodifieddate", "notes_last_updated", "createdate", "hubspot_owner_id", "hs_num_open_deals", "hs_total_deal_value"] limit: 5 ``` If a person name was provided: ``` Call: mcp__claude_ai_HubSpot__search_crm_objects Params: objectType: "contacts" filterGroups: [ { filters: [ { propertyName: "firstname", operator: "CONTAINS_TOKEN", value: "" }, { propertyName: "lastname", operator: "CONTAINS_TOKEN", value: "" } ]} ] properties: ["firstname", "lastname", "email", "jobtitle", "phone", "company", "hs_lead_status", "lifecyclestage", "createdate", "notes_last_updated", "hs_sales_email_last_replied", "hs_email_last_reply_date", "hubspot_owner_id", "hs_sequences_is_enrolled"] limit: 5 ``` If no person name was provided, search for all contacts associated with the company. ### Step 2: Pull All Data Sources (run in parallel) #### 2A. HubSpot — Deals ``` Call: mcp__claude_ai_HubSpot__search_crm_objects Params: objectType: "deals" filterGroups: [ { filters: [ { propertyName: "associations.company", operator: "EQ", value: "" } ]} ] properties: ["dealname", "amount", "dealstage", "pipeline", "closedate", "createdate", "hs_lastmodifieddate", "hubspot_owner_id", "hs_deal_stage_probability", "description", "notes_last_updated", "hs_is_closed_won", "hs_is_closed", "hs_acv", "hs_mrr"] limit: 20 ``` If company association search does not work, search by deal name containing the company name as a fallback. Also get deal stage names: ``` Call: mcp__claude_ai_HubSpot__get_properties Params: objectType="deals", propertyNames=["dealstage", "pipeline"] ``` #### 2B. HubSpot — Engagement History Search for contacts associated with the company to understand the full engagement timeline: ``` Call: mcp__claude_ai_HubSpot__search_crm_objects Params: objectType: "contacts" filterGroups: [ { filters: [ { propertyName: "company", operator: "CONTAINS_TOKEN", value: "" } ]} ] properties: ["firstname", "lastname", "email", "jobtitle", "phone", "hs_lead_status", "lifecyclestage", "createdate", "notes_last_updated", "hs_sales_email_last_replied", "hs_email_last_reply_date", "hs_email_sends_since_last_engagement", "num_notes", "num_contacted_notes", "hs_sequences_is_enrolled", "hs_analytics_num_page_views", "hs_analytics_num_visits"] limit: 20 ``` #### 2C. Fireflies — Past Meeting Transcripts Search for meetings with this company/person: ``` Call: mcp__claude_ai_Fireflies__fireflies_search Params: keyword: "" limit: 10 ``` Also try searching by person name if provided: ``` Call: mcp__claude_ai_Fireflies__fireflies_search Params: keyword: "" limit: 10 ``` For each relevant meeting found, pull the summary: ``` Call: mcp__claude_ai_Fireflies__fireflies_get_summary Params: transcriptId: "" ``` Extract from each meeting: - Key discussion topics and decisions - Pain points mentioned by the prospect/customer - Pricing or budget discussions (exact numbers) - Action items assigned to either party - Objections raised - Competitors mentioned - Timeline or urgency signals - Direct quotes that reveal priorities or concerns #### 2D. Apollo — Company Enrichment ``` Call: mcp__claude_ai_Apollo_io__apollo_organizations_enrich Params: domain: "" ``` Extract: - Company size (headcount, headcount growth) - Funding information (total raised, last round, investors) - Industry and sub-industry - Technology stack - LinkedIn URL - Key executives - Annual revenue estimate - Recent news or job postings If domain is not available, search by name: ``` Call: mcp__claude_ai_Apollo_io__apollo_mixed_companies_search Params: q_organization_name: "" per_page: 3 ``` #### 2E. Apollo — Contact Enrichment If a specific person is the meeting attendee: ``` Call: mcp__claude_ai_Apollo_io__apollo_people_match Params: email: "" ``` Or if no email: ``` Call: mcp__claude_ai_Apollo_io__apollo_mixed_people_api_search Params: q_person_name: "" q_organization_name: "" per_page: 3 ``` Extract: - Current title and seniority - LinkedIn profile URL - Previous companies and roles - Time in current role - Department #### 2F. Apollo — Job Postings (Buying Signals) ``` Call: mcp__claude_ai_Apollo_io__apollo_organizations_job_postings Params: organization_id: "" ``` Look for: - Hiring for roles related to Solum's value prop (billing, RCM, operations, tech) - Growth signals (lots of clinical hiring = scaling) - Pain signals (hiring for roles Solum could replace or augment) ### Step 3: Internal Fact-Check Layer Before assembling the brief, cross-reference data across sources. Check for and flag: #### Data Consistency - **Title mismatch**: Does the contact's title in HubSpot match Apollo? If not, note which is likely current. - **Company size discrepancy**: Does HubSpot's employee count match Apollo's? Flag if >20% difference. - **Deal amount vs. transcript**: If Fireflies transcripts mention specific pricing ($X/mo, $X/yr), compare against the HubSpot deal amount. Flag any discrepancy with exact quotes. - **Contact info**: Is the email/phone in HubSpot consistent with Apollo? #### Staleness Detection - **Deal stage age**: Calculate days in current stage. Flag if >30 days with a warning. - **Last activity gap**: Calculate days since last touchpoint (email, call, meeting, note). Flag if >14 days. - **Close date accuracy**: Is the close date in the past? Has it been pushed more than once? - **Stale contact data**: If HubSpot contact was last modified >90 days ago, note the data may be outdated. #### Action Item Tracking - Review action items from previous Fireflies meetings. - Cross-reference against HubSpot notes and activity timeline. - Classify each action item as: - **COMPLETED**: Evidence of follow-through in HubSpot activity or subsequent meeting - **PENDING**: No evidence of completion - **UNKNOWN**: Cannot determine status from available data #### Missing Data Flags - No deal associated with this company? Flag it. - No email history? Flag it. - No previous meetings? Note this is a first meeting. - Contact has no title? Flag for update. ### Step 4: Assemble the Brief Present the brief in this exact format. Keep it dense and scannable. No filler. ``` ================================================================ MEETING PREP: [Company Name] [Meeting Date if known] | Prepared [today's date] ================================================================ ATTENDEES --------- [Name] — [Title] (from [source: HubSpot/Apollo]) [Name] — [Title] LinkedIn: [URL if available] Email: [email] | Phone: [phone] Time in role: [X months/years, from Apollo] Previous: [previous company/role if notable] COMPANY SNAPSHOT ----------------- Industry: [industry] Size: [employee count] ([growth trend if available]) Location: [city, state] Founded: [year] Funding: [total raised / last round / investors] Revenue est: [if available from Apollo] EMR/Tech: [technology stack from Apollo] Domain: [website] LinkedIn: [company LinkedIn URL] Key facts: - [Notable fact 1 from Apollo enrichment] - [Notable fact 2] - [Recent job postings relevant to Solum] RELATIONSHIP HISTORY --------------------- First contact: [date from HubSpot createdate] Total touchpoints: [count of emails + calls + meetings + notes] Last interaction: [date and type — email/call/meeting] Days since last: [calculated] Timeline: [Date] — [Event: first email, first call, demo, proposal sent, etc.] [Date] — [Event] [Date] — [Event] ... DEAL STATUS ------------ Deal: [deal name] Stage: [current stage name] (since [date]) Days in stage: [calculated] [FLAG if >30 days] Amount: $[amount] ([monthly/annual]) Close date: [date] [FLAG if past due or pushed] Pipeline: [pipeline name] Probability: [%] Owner: [name] [If multiple deals, list each] [If no deal exists: "No deal record found — consider creating one after this meeting"] PREVIOUS MEETING HIGHLIGHTS ----------------------------- [Meeting date] — [meeting title] Key topics discussed: - [topic 1] - [topic 2] Their pain points (in their words): - "[direct quote from transcript]" - "[direct quote]" Decisions made: - [decision 1] Competitors mentioned: - [competitor name + context] Action items from this meeting: - [JP] [action item] — Status: [COMPLETED/PENDING/UNKNOWN] - [Prospect] [action item] — Status: [COMPLETED/PENDING/UNKNOWN] [Repeat for each past meeting, most recent first] [If no meetings found: "No previous meetings on record. This appears to be a first meeting."] THEIR PRIORITIES (from their own words) ----------------------------------------- Based on transcript analysis and email history: 1. [Priority 1 — with source: "quote" from meeting on date] 2. [Priority 2 — with source] 3. [Priority 3 — with source] [If no transcript data: "No direct quotes available. Priorities inferred from deal context and industry."] OPEN QUESTIONS / RISKS ------------------------ - [Unresolved question from past meetings] - [Risk factor: e.g., "No executive sponsor identified"] - [Risk factor: e.g., "Close date has been pushed twice"] - [Risk factor: e.g., "Competitor [X] was mentioned favorably in last call"] - [Missing info: "Budget not discussed yet"] - [Missing info: "Decision-making process unclear"] RECOMMENDED TALKING POINTS ---------------------------- Lead with: 1. [Specific opener based on their priorities and last interaction] 2. [Reference to specific pain point they mentioned] Address: 3. [Pending action item or follow-up from last meeting] 4. [Objection handling for known concerns] Advance the deal: 5. [Specific ask to move to next stage] 6. [Timeline or urgency angle based on their signals] Avoid: - [Topic or approach to stay away from, with reason] - [Sensitive area based on past interactions] FACT-CHECK NOTES ----------------- [List any discrepancies found during cross-referencing] - [e.g., "Title mismatch: HubSpot says 'Director of Ops', Apollo says 'VP Operations' — Apollo updated more recently, likely current"] - [e.g., "Deal amount is $50K in HubSpot but transcript from Feb 12 discussed $4K/month ($48K/yr) — minor discrepancy, verify on call"] - [e.g., "Action item from Jan meeting (send case study) — no evidence of completion in HubSpot"] [If no discrepancies: "All data consistent across sources."] DATA FRESHNESS --------------- HubSpot company: last modified [date] HubSpot contacts: last modified [date] HubSpot deal: last modified [date] Fireflies: [X] meetings found, most recent [date] Apollo: enrichment as of [today] ================================================================ ``` ## Error Handling - If HubSpot returns no company match: try alternate spellings, abbreviations, or domain search. If still nothing, note "Company not found in HubSpot" and continue with Apollo data. - If Fireflies returns no meetings: say "No previous meetings recorded." Continue with other sources. - If Apollo enrichment fails: skip the company snapshot details that require Apollo. Note the source was unavailable. - If any MCP tool fails: continue with available data. Note which sources were unavailable at the top of the brief. - Never skip the brief because one source failed. Deliver what you have, clearly noting gaps. ## Tone & Style - Dense, scannable, no fluff. This is a working document, not a narrative. - Data-first. Lead with facts, not opinions. - Direct quotes from transcripts are gold. Always include them when available. - Every recommendation must be grounded in data from the sources. No generic sales advice. - Flag unknowns explicitly. "Unknown" is better than a guess. - The entire brief should be readable in under 3 minutes. ## Post-Brief Actions After delivering the brief, ask: 1. "Want me to pull the full transcript from any of these meetings?" 2. "Should I update any stale data in HubSpot before your call?" 3. "Need me to draft any follow-up materials for after the meeting?"