# Train > Practice selling with role-play simulations, knowledge quizzes, and guided learning on your GTM library. Use when user says "role-play a call", "quiz me", "practice objections", "sales training", "test my knowledge", or asks for interactive learning. Use when this capability is needed. - Skill: `tomevault-io/train` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/train` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/train/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Marketing & Growth - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/train --- # /octave:train - Sales Training Ground Practice and learn your GTM playbook through interactive role-play simulations and knowledge quizzes — all grounded in your real library data. Role-play against buyer personas with realistic objections, or quiz yourself on value props, competitive positioning, and discovery techniques. ## Usage ``` /octave:train [mode] [--persona ] [--competitor ] [--difficulty easy|medium|hard] ``` ## Modes ``` /octave:train # Interactive - pick a mode /octave:train roleplay # Simulate a buyer conversation /octave:train roleplay --persona "CTO" # Role-play with a specific persona /octave:train roleplay --scenario discovery # Practice discovery calls /octave:train quiz # Test your GTM knowledge /octave:train quiz --topic objections # Quiz on objection handling /octave:train quiz --competitor "Acme" # Competitive knowledge check ``` ## Instructions When the user runs `/octave:train`: ### Step 1: Choose Mode If no mode specified, ask: ``` AskUserQuestion({ questions: [{ question: "What do you want to practice?", header: "Train mode", options: [ { label: "Role-Play", description: "Simulate a sales conversation — I'll play the buyer and give you feedback" }, { label: "Quiz", description: "Test your knowledge of personas, objections, value props, and competitive positioning" }, { label: "Guided Learning", description: "Walk me through a topic from your playbook — teach me like I'm a new hire" } ], multiSelect: false }] }) ``` --- ### Mode: Role-Play Simulate realistic buyer conversations using persona data from the library. #### Step RP-1: Setup the Scenario Ask for scenario parameters (use `AskUserQuestion` for structured choices): ``` AskUserQuestion({ questions: [ { question: "What scenario do you want to practice?", header: "Scenario", options: [ { label: "Discovery call", description: "First conversation — qualify the opportunity and uncover pain" }, { label: "Objection handling", description: "Practice responding to tough objections mid-deal" }, { label: "Demo pitch", description: "Present your product's value to a skeptical buyer" }, { label: "Competitive displacement", description: "Sell against a competitor the buyer currently uses" } ], multiSelect: false }, { question: "How tough should I be?", header: "Difficulty", options: [ { label: "Friendly", description: "Interested buyer, open to learning — good for building confidence" }, { label: "Skeptical (Recommended)", description: "Realistic buyer who pushes back and needs convincing" }, { label: "Hostile", description: "Tough buyer — time-pressed, has objections, hard to impress" } ], multiSelect: false } ] }) ``` If no persona specified, present available personas: ``` # Get personas from library list_all_entities({ entityType: "persona" }) ``` Ask: ``` AskUserQuestion({ questions: [{ question: "Which buyer persona should I play?", header: "Persona", options: [ { label: "[Persona 1 name]", description: "[Title] — [key concern]" }, { label: "[Persona 2 name]", description: "[Title] — [key concern]" }, { label: "[Persona 3 name]", description: "[Title] — [key concern]" } ], multiSelect: false }] }) ``` #### Step RP-2: Load Persona Intelligence ``` # Get full persona details get_entity({ oId: "" }) # Get matching playbook with value props search_knowledge_base({ query: " ", entityTypes: ["playbook"] }) get_playbook({ oId: "", includeValueProps: true }) # Get real objections from conversations (to make role-play realistic) list_findings({ query: "objections pushback concerns", startDate: "<180 days ago>", eventFilters: { personas: [""] } }) # Get product details list_all_entities({ entityType: "product" }) get_entity({ oId: "" }) # Get competitor details (for competitive scenarios) get_entity({ oId: "" }) // if competitive scenario # Get proof points (to evaluate if rep uses them) search_knowledge_base({ query: " results metrics", entityTypes: ["proof_point", "reference"] }) ``` #### Step RP-3: Set the Scene Present the scenario context, then begin: ``` ROLE-PLAY: [Scenario] with [Persona Name] ========================================== THE SCENE --------- You're on a [scenario type] with [Persona Name], [Title] at [fictional company]. About the buyer: - Role: [Title and responsibilities] - Company: [Brief fictional company description relevant to your ICP] - Situation: [Scenario-specific context] - Mood: [Based on difficulty level] About their company: - Industry: [From persona's typical segment] - Size: [Typical company size for this persona] - Current challenge: [Key pain point from persona data] [If competitive scenario:] - Currently using: [Competitor name] - Their satisfaction level: [Mixed/frustrated/somewhat happy] RULES ----- - I'll respond as the buyer would — using real objections from your conversation data - The conversation will last 8-12 exchanges - I'll end the conversation naturally when it reaches a conclusion - After the role-play, I'll give you a detailed scorecard --- The call starts now. [Persona Name] says: "[Opening line based on scenario and difficulty]" ``` **How to play the buyer:** Use the loaded persona data to respond realistically: - Reference real pain points from the persona entity - Raise real objections from conversation findings data - React based on difficulty level: - **Friendly**: Engaged, asks questions, shares information willingly - **Skeptical**: Needs proof, challenges claims, asks "why should I care?" - **Hostile**: Short answers, pushes on price, questions ROI, brings up competitors - Respond naturally to what the user says — don't just cycle through objections - If the user makes a strong point, acknowledge it (even skeptical buyers respond to good selling) - If the user fumbles, the buyer gets more distant/disengaged **End the conversation after 8-12 exchanges** with a natural conclusion: - Friendly: "This sounds interesting, let's set up a follow-up" - Skeptical: "I need to think about it" or "Send me some materials" - Hostile: "I don't think this is for us" (unless the user sold well) #### Step RP-4: Scorecard After the role-play ends, provide detailed feedback: ``` ROLE-PLAY SCORECARD ==================== Overall: [Score /100] Difficulty: [Friendly/Skeptical/Hostile] Scenario: [Type] --- WHAT YOU DID WELL ----------------- 1. [Specific thing they did well with quote from the conversation] 2. [Another strong moment] 3. [Good technique used] --- AREAS TO IMPROVE ----------------- 1. [Missed opportunity] — You could have said: "[Better response]" 2. [Weak moment] — Here's why: [Explanation] 3. [Technique to try] — "[Example of better approach]" --- ELEMENT SCORES -------------- | Element | Score | Notes | |---------|-------|-------| | Opening / rapport | [1-5] | [Brief feedback] | | Discovery questions | [1-5] | [Brief feedback] | | Pain identification | [1-5] | [Brief feedback] | | Value articulation | [1-5] | [Brief feedback] | | Proof point usage | [1-5] | [Brief feedback] | | Objection handling | [1-5] | [Brief feedback] | | Competitive positioning | [1-5] | [Brief feedback, if applicable] | | Call control | [1-5] | [Brief feedback] | | Next steps / CTA | [1-5] | [Brief feedback] | --- KEY MOMENTS ----------- Moment: "[Quote from the conversation]" Assessment: [What worked or didn't, with reference to playbook guidance] Moment: "[Another quote]" Assessment: [Feedback] --- OBJECTIONS ENCOUNTERED ----------------------- | Objection | Your Response | Ideal Response (from playbook) | |-----------|--------------|-------------------------------| | "[Objection 1]" | [What they said] | [What the playbook suggests] | | "[Objection 2]" | [What they said] | [Better approach] | --- PROOF POINTS YOU COULD HAVE USED ---------------------------------- - [Proof point from library that was relevant but not mentioned] - [Another unused proof point] --- Want to: 1. Try again (same scenario, apply the feedback) 2. Try a harder difficulty 3. Try a different persona 4. Practice a specific objection from this session 5. Switch to quiz mode 6. Done ``` --- ### Mode: Quiz Test knowledge of the user's own GTM library. #### Step Q-1: Choose Topic ``` AskUserQuestion({ questions: [{ question: "What do you want to be quizzed on?", header: "Quiz topic", options: [ { label: "Personas", description: "Pain points, priorities, buying triggers, and how to sell to each persona" }, { label: "Objection handling", description: "Common objections and how to respond — from your playbook and real conversations" }, { label: "Competitive positioning", description: "Differentiators, trap questions, and counters for each competitor" }, { label: "Full GTM review", description: "Mix of everything — personas, products, value props, objections, competitors" } ], multiSelect: false }] }) ``` Also ask for quiz format: ``` AskUserQuestion({ questions: [{ question: "What format?", header: "Format", options: [ { label: "Rapid fire (Recommended)", description: "Quick question-answer, 10 questions, scored at the end" }, { label: "Scenario-based", description: "Situational questions — 'A prospect says X, what do you do?'" }, { label: "Deep dive", description: "Fewer questions but explain your reasoning — I'll coach you on each answer" } ], multiSelect: false }] }) ``` #### Step Q-2: Load Quiz Material ``` # Load based on topic # For Personas: list_all_entities({ entityType: "persona" }) get_entity({ oId: "" }) // for each persona # For Objections: list_findings({ query: "objections pushback concerns pricing", startDate: "<180 days ago>" }) get_playbook({ oId: "", includeValueProps: true }) # For Competitive: list_all_entities({ entityType: "competitor" }) get_entity({ oId: "" }) // for each competitor # For Full GTM: list_all_entities({ entityType: "persona" }) list_all_entities({ entityType: "product" }) list_all_entities({ entityType: "competitor" }) search_knowledge_base({ query: "value propositions proof points" }) list_all_entities({ entityType: "use_case" }) ``` #### Step Q-3: Run the Quiz **Rapid Fire Format (10 questions):** Ask each question one at a time. After the user answers, score immediately, then move on. Question types per topic: **Personas:** - "What are the top 3 pain points for [Persona]?" - "What's the primary KPI that [Persona] is measured on?" - "Which value prop resonates most with [Persona]?" - "What's the best discovery question to open with for [Persona]?" - "What proof point would you use with [Persona]?" **Objections:** - "A prospect says '[Real objection from data]'. How do you respond?" - "What's the biggest pricing objection you'll face, and what's the counter?" - "A [Persona] says 'We're happy with what we have.' What do you say?" - "How do you handle 'It's too expensive' without discounting?" - "What reframe do you use when they say '[Feature] is missing'?" **Competitive:** - "What are our top 3 differentiators vs [Competitor]?" - "A prospect says '[Competitor] is cheaper.' How do you respond?" - "What trap question exposes [Competitor]'s weakness in [area]?" - "When should you NOT try to displace [Competitor]?" - "What proof point works best in a head-to-head against [Competitor]?" **Full GTM:** - Mix of all the above, rotating through topics Present each question as: ``` QUESTION [N]/10 =============== [Question text] Your answer: ``` After the user answers: ``` [Correct / Partially correct / Needs work] Your answer: "[Their answer summarized]" Best answer: "[From library data]" [Brief coaching note if needed] --- Next question... ``` **Scenario-Based Format (5 scenarios):** ``` SCENARIO [N]/5 ============== You're on a [call type] with [Persona Name], [Title] at a [company description]. [Setup: 2-3 sentences of context] They say: "[Realistic statement or objection from conversation data]" What do you do? (Describe your response and reasoning) ``` After the user answers, provide detailed coaching: ``` YOUR RESPONSE ------------- [Summary of what they said] ASSESSMENT: [Strong / Good / Needs work] What worked: - [Specific positive element] What to improve: - [Specific gap with coaching] Ideal approach: "[Best response from playbook + conversation evidence]" Why this works better: [Explanation tied to persona pain points and value props] ``` **Deep Dive Format (3 questions):** Same as rapid fire, but after each answer, enter a coaching dialogue: - Ask follow-up questions - Challenge their reasoning - Share what works from conversation data - Connect to playbook guidance #### Step Q-4: Quiz Results ``` QUIZ RESULTS ============= Score: [X]/[Total] ([Percentage]%) Topic: [Topic] Format: [Format] --- BREAKDOWN --------- | # | Question | Score | Notes | |---|----------|-------|-------| | 1 | [Brief question] | [Correct/Partial/Wrong] | [One-line note] | | 2 | [Brief question] | [Correct/Partial/Wrong] | [One-line note] | | ... | ... | ... | ... | --- STRENGTHS --------- - [Area where they scored well] - [Another strength] GAPS TO FOCUS ON ----------------- - [Topic they struggled with] — Review: [specific library entity or playbook section] - [Another gap] — Practice: [specific recommendation] --- RECOMMENDED NEXT STEPS ----------------------- 1. Review [specific entity] in your library: /octave:library show [entity] 2. Role-play [specific scenario] to practice: /octave:train roleplay --scenario [type] 3. Read the [playbook name] playbook for [gap area] --- Want to: 1. Retake this quiz 2. Try a different topic 3. Switch to role-play mode 4. Deep dive on a question I got wrong 5. Done ``` --- ### Mode: Guided Learning Walk through a topic from the library like a training session. #### Step GL-1: Choose Topic ``` AskUserQuestion({ questions: [{ question: "What do you want to learn about?", header: "Topic", options: [ { label: "A persona", description: "Deep walkthrough of how to sell to a specific buyer type" }, { label: "A competitor", description: "Learn competitive positioning, differentiators, and counters" }, { label: "A playbook", description: "Walk through a playbook's strategy, value props, and objection handling" }, { label: "Your product", description: "Master your product's capabilities, use cases, and proof points" } ], multiSelect: false }] }) ``` #### Step GL-2: Load and Teach Fetch the relevant entity and present it as a structured training walkthrough: ``` # Load the entity get_entity({ oId: "" }) # Load related playbook get_playbook({ oId: "", includeValueProps: true }) # Load real conversation examples list_findings({ query: "", startDate: "<180 days ago>" }) # Load proof points search_knowledge_base({ query: "", entityTypes: ["proof_point", "reference"] }) ``` Present as an interactive lesson: ``` TRAINING: Selling to [Persona Name] ===================================== LESSON 1: Who They Are ----------------------- [Overview of the persona — role, responsibilities, what they care about] Quick check: Can you name their top 3 priorities? (Try before scrolling down) Answer: 1. [Priority 1] 2. [Priority 2] 3. [Priority 3] --- LESSON 2: Their Pain Points ----------------------------- [Detailed pain points with context] From real conversations: - "[Quote from conversation findings]" — shows [insight] --- LESSON 3: How to Open ----------------------- [Best discovery questions for this persona] [What to listen for] [Common mistakes to avoid] --- LESSON 4: Value Props That Work --------------------------------- [Top value props from playbook, with proof points] From the field: - [What's been resonating in real conversations] - [What's NOT working] --- LESSON 5: Objections to Expect --------------------------------- [Common objections with responses] From real deals: - [Objections from won deals and how they were handled] - [Objections from lost deals and what went wrong] --- LESSON 6: Competitive Angles ------------------------------ [If competitors exist] [Key differentiators vs each competitor for this persona] --- SUMMARY CARD -------------- [Condensed reference card — everything above in 10 lines] --- Ready to test yourself? 1. Quick quiz on this persona 2. Role-play as this persona (I'll play the buyer) 3. Learn about a different topic 4. Done ``` ## MCP Tools Used ### Library Context - `list_all_entities` - List personas, products, competitors, use cases - `get_entity` - Full entity details (persona pain points, competitor weaknesses, etc.) - `get_playbook` - Playbook with value props, discovery questions, objection handling - `list_value_props` - Value propositions by persona - `search_knowledge_base` - Proof points, references, messaging ### Conversation Evidence - `list_findings` - Real objections, pain points, and signals from calls/emails - `list_events` - Deal outcomes (win/loss evidence for coaching) - `get_event_detail` - Specific interaction details for training examples ### Content Generation - `generate_content` - Generate scenario descriptions, coaching feedback ## Error Handling **No Personas in Library:** > No personas found in your library. > > Role-play and quizzes work best with persona data. > Add personas first: `/octave:library create persona` > > I can still run a general sales quiz using your product info. **No Conversation Data:** > No conversation data available yet. > > I'll use your library data for role-play and quizzes. > As your team logs calls and emails, training will get richer > with real-world objections and patterns. **No Competitors:** > No competitors in your library. > > Competitive quizzes and displacement role-plays need competitor data. > Add competitors: `/octave:library create competitor` > > I can still quiz you on personas, value props, and general objection handling. **Sparse Library:** > Your library has limited data for a full training session. > > Start with: > 1. `/octave:library create product` - Add your product > 2. `/octave:library create persona` - Add buyer personas > 3. `/octave:library create competitor` - Add competitors > > Even with just a product and one persona, I can run basic training. ## Related Skills - `/octave:enablement` - Generate training materials (cheat sheets, objection guides, discovery banks) - `/octave:battlecard` - Deep competitive intelligence for competitive training - `/octave:insights` - Surface real field intelligence to inform training - `/octave:wins-losses` - Win/loss patterns to learn from - `/octave:research` - Research a real prospect before a live call - `/octave:generate` - Generate real outreach after practicing --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/octavehq) — claim your Tome and manage your conversions.