industry-sector-analysis - SKILL.md Agent Skill

name: industry-sector-analysis version: "1.5.1" last_modified: "2026-03-22" description: | Use when assessing industry dynamics, cyclicality, sector-specific KPIs, competitive structure, or sector-adjusted credit risk before detailed issuer modeling. This skill frames what metrics matter, what a sector can support through the cycle, and which structural or documentation issues deserve extra scrutiny. category: sector-analysis related_skills: - credit-memo-generator - credit-modeling-and-valuation - credit-surveillance-monitoring - debt-structure-covenants - due-diligence-and-assessment - portfolio-investment-process - trading-pricing-mechanics triggers: - industry analysis - sector analysis - sector risk - industry dynamics - sector benchmarks - cyclical credit - defensive credit - industry-specific metrics - sector-specific red flags disambiguation: | Use this skill when the question is primarily about industry structure, sector behavior, peer context, or what operating metrics matter most. Use credit-modeling-and-valuation for issuer-specific forecasting, ratio analysis, and scenario mechanics. Use debt-structure-covenants for documentation analysis when the core issue is baskets, liens, leakage, or amendment risk. Use trading-pricing-mechanics for current spreads, market levels, or secondary pricing context. Use cre-analysis-underwriting when the asset is a property, real estate portfolio, or CRE loan rather than a corporate issuer.

Industry & Sector Analysis

Sector analysis provides the context around cyclicality, competitive structure, pricing power, regulation, and sector KPIs that determine what a credit can support through the cycle. Use it to frame the issuer before detailed modeling, documentation review, or surveillance work.

Core Workflow

Define the sector and value chain: Identify where the issuer sits in the value chain, which customers and inputs matter most, and whether the business behaves like the headline sector or a narrower sub-segment.
Place the sector in cycle context: Separate cyclical pressures from secular change and decide whether current performance reflects peak, mid-cycle, trough, or structural transition conditions.
Identify the 3-5 KPIs that actually drive credit quality: Focus on the operating metrics that explain revenue visibility, margins, working capital intensity, capital needs, and refinancing resilience.
Translate sector traits into credit implications: Convert cyclicality, pricing power, regulation, customer concentration, and capex intensity into leverage tolerance, downside severity, and likely recovery behavior.
Check rating and documentation pressure points: Note how agencies and lenders usually adjust for the sector, including lease treatment, addback risk, backlog quality, reserve assumptions, or regulated returns.
Stress the sector-specific risks: Pressure test the few variables that really matter rather than applying only generic top-line and margin shocks.
Hand off clear sector context: Pass cycle position, KPI interpretation, peer framing, and key red flags into modeling, covenant review, surveillance, or memo-writing work.

Reference Map

Read the narrowest relevant reference rather than loading the full library.

Default reading order

references/cross-asset-sector-framework.md — Start here: the five-dimension universal scaffold for cross-sector and cross-asset comparisons (corporate, private credit, CRE, infrastructure, structured finance).
references/sector-toolkit.md — Compact overlays: cyclical and secular framing, pricing power and pass-through, cross-sector comparison shortcuts, leverage calibration prompts, documentation watchpoints, and supply-chain vulnerability.
references/technology-disruption-timeline.md — Timing and debt-life lens: disruption horizons, maturity alignment, and refinancing-risk framing across industries. This is not a substitute for references/industry/technology.md, which holds the technology-sector operating detail, KPIs, and sub-sector deep dives. For property-type digital infrastructure, use references/industry/real-estate-data-centers.md for data centers and references/industry/real-estate-alternative.md for towers and related alternative real-estate digital infrastructure.
references/industry/*.md — Sector-specific files as needed (for example agribusiness-protein-fertilizer, aerospace-defense, automotive, banks, business-services, building-construction, capital-markets-asset-management, chemicals, consumer-finance, energy-midstream, environmental-services-waste, financial-services, food-beverage, gaming-leisure-hospitality, healthcare, household-personal-care-consumer-products, industrials-manufacturing, insurance, media, metals-mining, packaging, paper-forest-products, payments-fintech, pharma-biotech-medtech, power-generation-renewables, real-estate-alternative, real-estate-data-centers, real-estate-hotels, real-estate-industrial-logistics, real-estate-office, real-estate-residential, real-estate-retail, retail-consumer, specialty-finance-leasing, technology, telecom, tobacco, transportation-logistics, and utilities-infrastructure).

Output Deliverables

When asked to analyze a sector or provide industry context for a credit, produce:

Source citations: Explicitly cite all data, qualitative claims, and benchmark inputs.
- When a stable direct URL exists, include it inline with the citation and keep any page, slide, filing-date, report-date, or access-date detail in the same citation.
Sector framing: Market structure, cycle position, and whether the key issue is cyclical, secular, regulatory, or company-specific.
Key credit metrics: The sector-specific KPIs that matter most and how to interpret them.
Sector-adjusted leverage view: What the sector can generally support, using references/rating-agency-thresholds.md for any current numerical calibration.
Agency and structural watchpoints: What agencies and lenders usually focus on for this sector.
Common red flags: The operating or structural warning signs that most often precede credit deterioration.
Stress implications: The few downside scenarios most likely to break the thesis.
Handoff inputs: Clear takeaways for modeling, covenant review, surveillance, or memo writing.

Limitations

Sector labels can hide more than they reveal; some issuers behave like a niche sub-sector rather than the headline industry.
Sector heuristics are starting points, not rating outcomes; issuer-specific positioning, financial policy, and documentation still dominate final credit judgment.
Benchmark ranges are least useful at cyclical peaks, during structural transition, or when accounting treatment materially distorts reported EBITDA.
For broader framework limitations, consult skills/credit-memo-generator/references/analytical-limitations.md.

Data Quality

When data is incomplete or unavailable, consult skills/credit-memo-generator/references/incomplete-data-guidance.md for gap disclosure templates. Never silently fill gaps with assumptions.
If the answer depends on current spread levels, current rating calibration, or current documentation conditions, use the relevant root reference rather than relying on timeless sector notes.
When applying standard analytical frameworks, consult skills/credit-memo-generator/references/analytical-limitations.md to identify when the framework may produce unreliable results. Disclose limitations proactively rather than presenting framework outputs as authoritative.

Examples

examples/worked-sector-analysis-example.md: Sector analysis for business services showing market structure, cycle framing, key KPIs, sector risks, and sector-adjusted credit interpretation.