skills/octagonai/skills/earnings-analyst-questions

earnings-analyst-questions

SKILL.md

Earnings Analyst Questions

Identify and analyze the key themes, concerns, and questions raised by analysts during earnings calls, with specific analyst attribution and topic categorization.

Prerequisites

Ensure Octagon MCP is configured. See references/mcp-setup.md for installation instructions.

Workflow

Step 1: Extract Analyst Questions

Use the Octagon MCP to identify analyst questions and concerns:

Identify key themes and concerns raised by analysts during <TICKER>'s latest earnings call.

Step 2: Targeted Question Analysis

Focus on specific aspects of analyst questions:

# All Analyst Concerns
What concerns did analysts raise in <TICKER>'s latest earnings call?

# Specific Topic
What questions did analysts ask about AI in <TICKER>'s earnings call?

# Analyst Coverage
Which analysts participated in <TICKER>'s earnings call Q&A?

# Most Frequent Topics
What were the most frequently asked topics in <TICKER>'s earnings call?

# Unanswered Questions
Were there questions that management avoided or didn't fully answer in <TICKER>'s call?

Expected Output

The skill returns structured analyst question analysis including:

Component Description
Key Themes Major topics raised by analysts
Analyst Attribution Which analyst asked which question
Concern Categories Grouped by topic area
Management Response How questions were addressed
Follow-up Questions AI-generated questions for deeper research
Source Citations Transcript page references

Example Query

Identify key themes and concerns raised by analysts during TSLA's latest earnings call.

Example Response

Analysts highlighted several critical topics during Tesla's latest earnings call, as documented in the TSLA_Q22025 transcript:

Key Analyst Questions

  • Robotaxi Business Funding – Analysts questioned how Tesla plans to finance the costs of scaling its robotaxi initiative, specifically whether it will rely on auto business cash flows or alternative funding sources [Dan Meir Levy]

  • Full Self-Driving (FSD) Revenue Potential – Interest focused on trends and monetization strategies for FSD subscriptions [Mark Trevor Delaney]

  • Megapack Sales Impact – The elimination of tax credits for solar projects raised concerns about its effect on Tesla's Megapack sales pipeline

  • Incentive Loss and Autonomy Challenges – Analysts warned of potential rough quarters due to the loss of U.S. incentives and the early-stage risks of autonomy development [Elon Musk]

  • Lower-Cost Model Details – Requests for more information on production timelines and cost-saving strategies for Tesla's upcoming lower-cost vehicle [Lars Moravy]

Follow-up Questions

  • What specific funding mechanisms has Tesla outlined for the robotaxi business?
  • How does Tesla plan to mitigate risks from the loss of U.S. tax incentives?
  • What are the projected timelines for the lower-cost model's production launch?

Source: TSLA_Q22025, Page: 5

Analyst Question Categories

Financial Topics

Category Example Questions
Revenue Segment growth, pricing, demand
Margins Cost structure, pricing power
Guidance Outlook clarification, assumptions
Capital Allocation, returns, leverage

Strategic Topics

Category Example Questions
Growth Initiatives New products, markets, investments
Competitive Market share, differentiation
M&A Deal pipeline, integration
Technology R&D, innovation, roadmap

Operational Topics

Category Example Questions
Execution Production, capacity, efficiency
Supply Chain Sourcing, costs, risks
Workforce Hiring, retention, costs
Geographic Regional performance, expansion

Risk Topics

Category Example Questions
Regulatory Policy changes, compliance
Macro Economic sensitivity, cycles
Competitive Market threats, disruption
Execution Delivery, timeline risks

Analyst Attribution

Understanding Analyst Context

Analyst Type Typical Focus
Sell-side (Bulge Bracket) Broad coverage, key themes
Sell-side (Boutique) Sector expertise, detailed
Buy-side Specific thesis questions
Independent Alternative perspectives

Notable Analyst Patterns

Pattern Interpretation
Same analyst, same topic Persistent concern
Multiple analysts, same topic Widespread concern
New topic raised Emerging issue
Detailed follow-up Dissatisfied with response

Question Intensity Analysis

Measuring Topic Importance

Metric Interpretation
Number of questions Topic priority
Number of follow-ups Incomplete answers
Analyst seniority Credibility weight
Time spent Management engagement

Heat Map Framework

Topic Questions Follow-ups Intensity
FSD Revenue 3 2 High
Margins 2 1 Medium
CapEx 1 0 Low

Concern Classification

Severity Assessment

Severity Indicators
Critical Multiple analysts, pushback, unresolved
High Several questions, detailed probing
Medium Standard questions, adequate response
Low Single mention, brief discussion

Resolution Status

Status Description
Resolved Clear, specific answer provided
Partially Resolved Some detail, gaps remain
Deflected Redirected, not directly answered
Unresolved Avoided, promised future update

Tracking Questions Over Time

Quarter-over-Quarter Analysis

Topic Q1 Q2 Q3 Q4 Trend
FSD 1 2 3 4 Rising
Margins 3 2 2 1 Declining
China 2 3 2 2 Stable

New vs. Recurring Topics

Type What It Means
New topic Emerging concern or opportunity
Recurring topic Persistent issue
Dropped topic Resolved or no longer relevant
Intensifying Growing importance

Use Cases

  1. Sentiment Analysis: Gauge Street concerns and focus areas
  2. Risk Discovery: Identify issues analysts are probing
  3. Thesis Validation: Check if your concerns are shared
  4. Peer Comparison: Compare question themes across competitors
  5. Management Assessment: Evaluate response quality
  6. Pre-Earnings Prep: Anticipate likely questions

Combining with Other Skills

Skill Combined Analysis
earnings-qa-analysis Questions + management responses
earnings-call-analysis Full context + analyst focus
price-target-consensus Analyst concerns vs. targets
stock-grades Questions aligned with ratings
stock-price-change Question impact on price

Analysis Tips

  1. Track Analyst Names: Note who asks what repeatedly

  2. Count Question Frequency: More questions = higher priority

  3. Watch for Pushback: Analysts pressing = important issue

  4. Note Unanswered Questions: What's management avoiding?

  5. Compare to Peers: Are same questions asked of competitors?

  6. Pre-Earnings Prediction: Anticipate topics based on history

Interpreting Results

See references/interpreting-results.md for detailed guidance on analyzing analyst questions.

Weekly Installs
21
GitHub Stars
11
First Seen
Feb 7, 2026
Installed on
opencode21
gemini-cli20
codex20
github-copilot19
cursor19
amp18