/octave:analyzer - Conversation Analysis

Analyze email threads, call transcripts, and sales conversations against your Octave library. Evaluates messaging resonance, playbook adherence, and competitive differentiation. Provides actionable insights, suggested improvements, and draft follow-ups.

Usage

/octave:analyzer [--type email|call|chat]

Examples

/octave:analyzer                              # Interactive - paste content
/octave:analyzer --type email                 # Analyze email thread
/octave:analyzer --type call                  # Analyze call transcript

Instructions

When the user runs /octave:analyzer:

Step 1: Get Content to Analyze

What would you like me to analyze?

1. Paste an email thread
2. Paste a call transcript
3. Paste a chat/message thread
4. Provide a file path

(Paste content below or tell me the file path)

Accept pasted content or read from file. Content can be:

• Email thread (with headers or without)
• Call transcript (with speaker labels or without)
• Chat/messaging thread
• Meeting notes

Step 2: Parse and Structure the Content

For Email: Extract:

• Participants (internal vs external)
• Thread direction (outbound, inbound, back-and-forth)
• Key messages from each party
• Current status (awaiting response, ended, etc.)

For Call Transcript: Extract:

• Participants and roles
• Speaker segments
• Key exchanges
• Duration indicators if available

For Chat: Extract:

• Participants
• Message sequence
• Key exchanges

Step 3: Identify Context

Use MCP tools to gather context:

Research external participants:

# Get external participant info
find_person({
  searchMode: "specific_person",
  email: "<external email>",  # or
  firstName: "<name>",
  companyName: "<company>"
})

# Get company info
find_company({
  domain: "<domain from email>"  # or inferred from signature
})

# Match to persona
qualify_person({
  person: { email: "<email>", jobTitle: "<title>" },
  additionalContext: "Identify which persona this person matches"
})

Get library context:

# Find relevant playbook
search_knowledge_base({
  query: "<key topics from conversation>",
  entityTypes: ["playbook"]
})

Step 4: Analyze Against Library

Run three analysis dimensions:

---

Resonance Analysis

Did our messaging land? What signals indicate engagement or disengagement?

Use MCP to get persona details:

# Search for messaging we used
search_knowledge_base({
  query: "<key phrases from our messages>",
  entityTypes: ["persona", "playbook", "use_case"]
})

# Compare to persona pain points
get_entity({ oId: "<matched_persona_oId>" })

Evaluate:

• Pain points addressed vs. persona's documented pain points
• Value props used vs. available value props
• Questions asked vs. recommended discovery questions
• Response patterns indicating interest/skepticism

---

Adherence Analysis

Did we follow the playbook? What did we miss?

Use MCP to get playbook details:

# Get the relevant playbook
get_playbook({ oId: "<matched_playbook_oId>", includeValueProps: true })

Compare conversation to playbook:

• Strategic narrative alignment
• Value props delivered vs. available
• Qualifying questions asked
• Objection handling approach
• Discovery depth

---

Differentiation Analysis

Did we position against competitors effectively?

Use MCP to get competitor details:

# Check for competitor mentions
search_knowledge_base({
  query: "<competitor names or hints from conversation>",
  entityTypes: ["competitor"]
})

# Get competitor details
get_entity({ oId: "<competitor_oId>" })

Evaluate:

• Competitor mentions (explicit or implicit)
• Our differentiation points used vs. available
• Landmines set or missed
• Competitive traps addressed

Step 5: Generate Analysis Report

CONVERSATION ANALYSIS
=====================

Analyzed: [Email thread / Call transcript / Chat]
Date: [If available]
Duration/Length: [X messages / X minutes]

---

PARTICIPANTS
------------
Internal:
• [Name] ([Role]) - [# of messages/speaking time]

External:
• [Name] ([Title] at [Company]) - [# of messages/speaking time]
  Matched Persona: [Persona name] ([Confidence])

---

CONTEXT IDENTIFIED
------------------
Company: [Company name]
ICP Fit: [Score/100]
Stage: [Discovery / Demo / Negotiation / etc.]
Playbook Match: [Playbook name]

---

EXECUTIVE SUMMARY
-----------------
[2-3 sentence summary of what happened, key outcomes, and overall assessment]

---

RESONANCE ANALYSIS
==================
Score: [X/10] - [Strong / Moderate / Weak]

What Resonated (Positive Signals):
✓ [Signal 1] - [Quote or evidence]
  "[Exact quote from prospect showing interest]"

✓ [Signal 2] - [Quote or evidence]
  "[Exact quote showing engagement]"

What Didn't Land (Concerns):
✗ [Issue 1] - [Quote or evidence]
  "[Quote showing skepticism or disengagement]"
  Suggestion: [How to address this]

✗ [Issue 2] - [Quote or evidence]
  Suggestion: [How to address this]

Pain Points Addressed:
┌──────────────────────────────────────────────┐
│ Persona Pain Point          │ Addressed?     │
├──────────────────────────────────────────────┤
│ [Pain point 1]              │ ✓ Yes          │
│ [Pain point 2]              │ ✗ No           │
│ [Pain point 3]              │ ~ Partially    │
└──────────────────────────────────────────────┘

Recommendations:
• [Specific action to improve resonance]
• [Topic to explore in next conversation]

---

ADHERENCE ANALYSIS
==================
Score: [X/10] - [Strong / Moderate / Weak]
Playbook: [Playbook name]

Playbook Elements Used:
✓ [Element 1] - Used effectively
✓ [Element 2] - Used effectively

Playbook Elements Missed:
✗ [Element 3] - Not addressed
  Why it matters: [Impact of missing this]
  Add in follow-up: [Suggestion]

✗ [Element 4] - Not addressed
  Why it matters: [Impact]
  Add in follow-up: [Suggestion]

Value Props Delivered:
┌────────────────────────────────────────────────────┐
│ Value Prop                   │ Delivered? │ Impact │
├────────────────────────────────────────────────────┤
│ [VP 1 for this persona]      │ ✓ Strong   │ Positive │
│ [VP 2 for this persona]      │ ✗ No       │ Opportunity │
│ [VP 3 for this persona]      │ ~ Weak     │ Reinforce │
└────────────────────────────────────────────────────┘

Discovery Questions:
┌─────────────────────────────────────────────────┐
│ Recommended Question          │ Asked? │ Answer │
├─────────────────────────────────────────────────┤
│ [Question 1 from playbook]    │ ✓ Yes  │ [Summary] │
│ [Question 2 from playbook]    │ ✗ No   │ -         │
│ [Question 3 from playbook]    │ ✗ No   │ -         │
└─────────────────────────────────────────────────┘

Recommendations:
• Ask "[missed question]" in follow-up
• Reinforce "[underdelivered value prop]" with proof point

---

DIFFERENTIATION ANALYSIS
========================
Score: [X/10] - [Strong / Moderate / Weak]

Competitors Detected:
• [Competitor 1] - [How mentioned: explicit / implicit / inferred]
• [Competitor 2] - [How mentioned]

Differentiation Points Used:
✓ [Differentiator 1] - "[Quote where we differentiated]"
✓ [Differentiator 2] - "[Quote]"

Differentiation Opportunities Missed:
✗ [Differentiator 3] - Not mentioned
  When to use: [Trigger from conversation where this would fit]

✗ [Differentiator 4] - Not mentioned
  When to use: [Trigger]

Competitive Positioning:
┌────────────────────────────────────────────┐
│ Our Differentiator    │ Mentioned? │ Impact │
├────────────────────────────────────────────┤
│ [Diff 1 vs competitor]│ ✓ Yes      │ Strong │
│ [Diff 2 vs competitor]│ ✗ No       │ Missed │
│ [Diff 3 vs competitor]│ ✗ No       │ Missed │
└────────────────────────────────────────────┘

Competitive Risks:
⚠ [Risk identified from conversation]
  Counter: [How to address]

Recommendations:
• In follow-up, plant this landmine: "[Question that exposes competitor weakness]"
• Reference: "[Proof point of competitive win]"

---

ACTION ITEMS IDENTIFIED
=======================

From Prospect (They Committed To):
□ [Action item prospect mentioned]
□ [Action item prospect mentioned]

From Us (We Should Do):
□ [Action we committed to]
□ [Implied action to take]

Open Questions (Need Answers):
? [Unresolved question from conversation]
? [Question we should have asked]

---

FOLLOW-UP RECOMMENDATIONS
=========================

Immediate (Within 24 Hours):
1. [Specific action]
   Why: [Reason/urgency]

This Week:
2. [Action to advance the conversation]
3. [Content to send based on conversation]

Topics for Next Conversation:
• [Topic 1 to address]
• [Topic 2 to explore]
• [Objection to preempt]

---

SUGGESTED FOLLOW-UP MESSAGE
===========================

Based on this conversation, here's a draft follow-up:

---
Subject: [Subject line]

[Personalized opening referencing specific moment from conversation]

[Address any open questions or commitments]

[Reinforce key value prop that resonated]

[Add missed value prop or proof point naturally]

[Clear next step / CTA]

[Sign off]
---

Want me to:
1. Refine this follow-up
2. Create a different style of follow-up
3. Generate content for a specific gap identified
4. Analyze another conversation

Step 6: Offer Refinements

What would you like to do next?

1. Deep dive on a specific analysis area
2. Get more suggestions for [resonance / adherence / differentiation]
3. Refine the follow-up message
4. Generate content to address gaps
5. Compare to another conversation
6. Save insights to deal notes
7. Done

Your choice:

Analysis Scoring Guide

Resonance Score (1-10)

Score	Meaning	Signals
9-10	Strong engagement	Multiple questions, shared details, expressed urgency
7-8	Good engagement	Engaged responses, some interest signals
5-6	Neutral	Polite but non-committal
3-4	Weak	Short responses, delayed replies
1-2	Disengaged	Objections, pushback, ghosting

Adherence Score (1-10)

Score	Meaning	Signals
9-10	Full adherence	All playbook elements used appropriately
7-8	Good adherence	Most elements used, minor gaps
5-6	Partial adherence	Some elements used, key gaps
3-4	Weak adherence	Few elements used, off-playbook
1-2	Non-adherent	Didn't follow playbook approach

Differentiation Score (1-10)

Score	Meaning	Signals
9-10	Strong positioning	Clear differentiation, competitive landmines set
7-8	Good positioning	Some differentiation, mostly positioned
5-6	Neutral	Didn't address competition directly
3-4	Weak positioning	Competitor strengths uncountered
1-2	Poor positioning	Lost competitive ground

MCP Tools Used

Research

• find_person - Identify external participants
• find_company - Get company context
• qualify_person - Match to persona

Library Context

• get_playbook - Get playbook for adherence analysis
• get_entity - Get persona, competitor details
• search_knowledge_base - Find relevant messaging, proof points

Content Generation

• generate_content - Draft follow-up messages
• generate_email - Generate email responses

Input Formats Supported

Email Thread

From: john@acme.com
To: me@company.com
Subject: Re: Quick question about your platform

[Message content]

---
On Jan 15, me@company.com wrote:
> [Previous message]

Call Transcript

[00:00] Sales Rep: Thanks for joining...
[00:15] Prospect: Happy to be here...

or

Sales Rep: Thanks for joining...
John (Acme): Happy to be here...

Chat/Message Thread

Me: Hey John, following up on our conversation
John: Thanks for reaching out
Me: Did you have a chance to review the proposal?

Error Handling

No Content Provided:

Please paste the content you'd like me to analyze, or provide a file path.

I can analyze:

• Email threads
• Call transcripts
• Chat messages
• Meeting notes

Cannot Identify Participants:

I couldn't identify the external participant.

Can you tell me:

1. Who is the prospect? (name, company, title)
2. What stage is this deal in?

This helps me match to the right persona and playbook.

No Matching Playbook:

I couldn't find a playbook that matches this conversation.

I'll analyze against general best practices, but for better insights:

• Create a relevant playbook (/octave:library create playbook)
• Or tell me which playbook should apply

Related Skills

• /octave:research - Deep research on participants
• /octave:generate - Generate follow-up content
• /octave:pmm - Create collateral to address gaps
• /octave:audit - Ensure playbooks have complete guidance
• /octave:pipeline - Deal coaching based on conversation analysis
• /octave:insights - Aggregate patterns across many conversations