analyzing-sector-theses
Develops investment sector theses with market mapping, trend analysis, and opportunity identification. Use when building sector strategies, mapping target markets, or identifying investment themes.
Best use case
analyzing-sector-theses is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Develops investment sector theses with market mapping, trend analysis, and opportunity identification. Use when building sector strategies, mapping target markets, or identifying investment themes.
Teams using analyzing-sector-theses 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/analyzing-sector-theses/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How analyzing-sector-theses Compares
| Feature / Agent | analyzing-sector-theses | 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?
Develops investment sector theses with market mapping, trend analysis, and opportunity identification. Use when building sector strategies, mapping target markets, or identifying investment themes.
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
# Analyzing Sector Theses Develops investment sector theses with market mapping, trend analysis, and opportunity identification for PE, VC, and growth equity strategies. ## When To Use - Building or refining a sector-specific investment strategy for fund deployment - Mapping a target market to identify acquisition or investment candidates - Evaluating whether a macro trend (regulatory shift, technology cycle, demographic change) creates a durable investment theme - Preparing an IC memo section that frames the sector rationale behind a specific deal - Comparing adjacent sectors to prioritize capital allocation across a portfolio ## Inputs To Gather - **Sector definition**: Industry vertical, NAICS/SIC codes, or descriptive boundaries (e.g., "specialty chemicals excluding commodity petrochemicals") - **Investment lens**: Buyout, growth equity, or venture; control vs. minority; target hold period - **Market data**: TAM/SAM/SOM estimates, historical growth rates, margin profiles by sub-segment - **Competitive landscape**: Key incumbents, recent transaction activity (M&A, IPO, SPAC), sponsor ownership map - **Macro drivers**: Regulatory catalysts, technology adoption curves, demographic or supply-chain shifts - **Fund constraints**: Check size range, geographic focus, sector exclusions, LP mandate restrictions - **Existing portfolio context**: Current sector exposures, platform companies seeking add-ons, prior thesis documents to build on ## Workflow 1. **Define sector boundaries** — Establish precise inclusion/exclusion criteria. Distinguish the investable universe from the broader industry. Identify sub-segments worth separate treatment (e.g., within "healthcare IT," separate EHR, RCM, clinical decision support). 2. **Size and profile the market** — Compile TAM/SAM estimates with source attribution. Chart historical revenue growth, EBITDA margins, and capital intensity across sub-segments. Flag where data is estimated vs. confirmed [VERIFY market size sources and vintage]. 3. **Map the competitive landscape** — Identify the top 10–20 players by revenue or market share. Note ownership (public, founder-owned, sponsor-backed) and recent capital events. Build a sponsor activity heat map showing who has invested, at what multiples, and exit outcomes. 4. **Identify secular drivers and risks** — Catalog 3–5 macro tailwinds (e.g., aging population, reshoring, AI adoption) with evidence of durability. Equally catalog headwinds (regulatory risk, cyclicality, customer concentration). Assess which drivers are priced into current multiples vs. underappreciated. 5. **Develop the thesis statement** — Articulate the core investment hypothesis in 2–3 sentences: why this sector, why now, and what the value-creation playbook looks like (organic growth, buy-and-build, margin expansion, multiple arbitrage). Specify the target company profile (revenue range, growth rate, margin floor, geographic footprint). 6. **Screen the opportunity set** — Apply thesis criteria to the competitive map. Rank potential targets by strategic fit, estimated availability, and rough valuation expectations. Flag platform vs. add-on candidates. 7. **Stress-test and challenge** — Identify the top 3 reasons the thesis could fail. Assess downside scenarios (margin compression, regulatory reversal, technology disruption). Compare thesis conviction level against competing sectors for the same capital. ## Output Produce a **Sector Thesis Memo** containing: - **Executive summary**: 1-paragraph thesis statement with target return profile - **Market overview**: Size, growth, segmentation, and margin landscape with sourced data - **Competitive map**: Visual or tabular view of key players, ownership, and recent transactions - **Secular drivers**: Ranked list of tailwinds and headwinds with supporting evidence - **Investment criteria**: Target company profile (size, growth, margins, geography, ownership structure) - **Opportunity pipeline**: Preliminary list of 10–30 potential targets ranked by fit - **Key risks and mitigants**: Top failure modes with proposed hedges or diligence focus areas - **Appendix**: Data sources, methodology notes, and items flagged [VERIFY] ## Quality Checks - Every market size figure has a cited source and date; estimates older than 2 years are flagged [VERIFY] - Thesis statement is falsifiable — it identifies specific conditions under which the thesis breaks - Competitive map covers at least 80% of the addressable market by revenue - Sponsor activity data includes entry multiples and hold periods where available [VERIFY transaction multiples against public sources] - Sub-segment analysis avoids treating heterogeneous businesses as a monolith (e.g., separating software from services revenue) - Target screening criteria are concrete enough to run against a database (revenue range, geography, ownership type) — not vague qualitative descriptors - Risks section includes at least one structural risk (not just cyclical or execution risk) - Output distinguishes between confirmed data and directional estimates throughout
Related Skills
analyzing-vital-statistics
Structures vital records analysis with birth, death, and demographic trend reporting. Use when analyzing vital statistics, interpreting mortality data, or reporting demographic trends.
analyzing-social-determinants-of-health
Maps social determinants affecting health outcomes with intervention strategy development. Use when analyzing SDOH, mapping community resources, or designing social health interventions.
analyzing-pharmacovigilance-data
Structures post-marketing safety surveillance with signal detection and PSUR reporting. Use when analyzing safety signals, preparing PSURs, or managing pharmacovigilance data.
analyzing-flow-cytometry
Interprets flow cytometry panels for hematologic malignancy classification and minimal residual disease. Use when analyzing flow cytometry, classifying lymphomas/leukemias, or documenting immunophenotyping.
analyzing-epidemiological-data
Structures epidemiologic analysis with incidence, prevalence, rate calculations, and statistical inference. Use when calculating disease rates, analyzing epi data, or interpreting population statistics.
analyzing-clinical-trial-data
Structures clinical trial data analysis with primary endpoint evaluation and safety reporting. Use when analyzing trial results, evaluating endpoints, or preparing statistical reports.
analyzing-clinical-data-warehouses
Structures clinical data warehouse queries for quality measurement, research, and operational analytics. Use when querying clinical data, building analytics reports, or extracting research datasets.
tracking-sector-rotation
Monitors sector performance rotation with factor exposure and macro sensitivity analysis. Use when tracking sector rotation, analyzing factor exposures, or identifying sector trends.
analyzing-yield-curves
Interprets yield curve shapes with term structure analysis and relative value identification. Use when analyzing yield curves, identifying curve trades, or interpreting interest rate expectations.
analyzing-wealthtech-platforms
Evaluates wealth management technology with robo-advisory models, digital planning, and fee analysis. Use when analyzing wealthtech, evaluating robo-advisors, or assessing digital wealth platforms.
analyzing-water-risk
Structures water risk assessment with water stress mapping, usage analysis, and regulatory exposure evaluation. Use when analyzing water risk, mapping water stress, or evaluating water-related financial exposure.
analyzing-volatility-surfaces
Constructs and interprets implied volatility surfaces with skew analysis and term structure assessment. Use when analyzing vol surfaces, interpreting skew, or modeling volatility dynamics.