earnings-analyst-questions
Identify key themes and concerns raised by analysts during earnings calls, including specific analyst attribution and topic categorization.
Best use case
earnings-analyst-questions is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Identify key themes and concerns raised by analysts during earnings calls, including specific analyst attribution and topic categorization.
Teams using earnings-analyst-questions should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/earnings-analyst-questions/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How earnings-analyst-questions Compares
| Feature / Agent | earnings-analyst-questions | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Identify key themes and concerns raised by analysts during earnings calls, including specific analyst attribution and topic categorization.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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](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](references/interpreting-results.md) for detailed guidance on analyzing analyst questions.
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