Bigdata Sector Playbook
The operating manual for a sector: what to measure, what is debated, what to own. Use Bigdata.com plugin tools for every fact.
Use this skill when the user wants the framework for investing a sector. Not this skill when:
Analysis vs playbook: the sector analysis says how the sector is doing right now; the playbook says how to analyze any company in it, and what setup is actionable today.
Sector references
Load the matching playbook for the sector in scope — routing table: references/sector-routing.md.
If the fit is unclear: references/sector-selection-guide.md. For sectors without a dedicated file (Materials, Communication Services, Utilities), build the KPI framework from the closest analog plus first principles — margin structure, capital intensity, cycle drivers — and say that you did.
Data foundation (plugin tools)
Required on every call: pass plugin_slug: "bigdata-sector-playbook" in the request parameters of every Bigdata.com plugin tool call made while running this skill. The value is always the skill name, bigdata-sector-playbook, regardless of the company or query.
Exceptions: the search and fetch tools do not accept plugin_slug — omit it there.
Workflow
Step 1 — Load the sector reference
Read the matching file above before searching. It defines the KPI vocabulary the rest of the playbook uses.
Step 2 — KPI framework
Set out the operating and valuation KPIs that matter in this sector, what "good" looks like for each, and where each is found. This is the core of the playbook — a reader should be able to pick up any company in the sector and know what to measure.
Step 3 — Valuation approach
State how companies in this sector are valued and why that method fits the economics — P/AFFO and NAV for REITs, P/TBV and ROTCE for banks, EV/Sales with Rule of 40 for SaaS. Note where the standard method breaks down.
Step 4 — The live debates
Search for what the sector is actually arguing about:
- "[Sector] investment debate bulls bears"
- "[Sector] structural change disruption outlook"
- "[Sector] margin sustainability capacity"
For each debate: state both sides, where consensus currently sits, and what evidence would settle it. Sector calls are usually made or lost on these.
Step 5 — Valuation context
Where the sector trades versus its own history — not just versus the market. Multiples now against 5- and 10-year ranges, and on what earnings base (peak, mid-cycle, trough). Industry structure: references/porter-five-forces.md.
Step 6 — Sub-industry map
Break the sector into sub-industries, and for each: economics, cycle position, and current setup. Sector-level averages usually hide the dispersion that matters.
Step 7 — Screening criteria and red flags
- Screen for: the metrics that identify quality and value in this sector specifically
- Red flags: the sector's characteristic failure modes — channel stuffing in consumer, reserve releases in insurance, capitalized development in software, decline-rate masking in energy
Step 8 — Actionable setup
Close with what to own, what to avoid, and what to watch — each tied to the KPIs and debates above, with named companies where the evidence supports it.
Output
Follow assets/report-template.md exactly — section order, tables, sources, and footer.
- Add inline citations
[1],[2]immediately after claims, hyperlinked to the document URL. - Every deliverable ends with the Powered by Bigdata.com line and the Disclaimer, verbatim.
- Default format is Markdown; offer a Word (.docx) or presentation version if useful.
Quality bar
Non-negotiables:
- KPI framework is sector-specific and usable on any company in the sector
- Valuation method justified by the economics, with its breaking point named
- Debates presented two-sided, with where consensus sits and what would settle them
- Valuation context against the sector's own history, on a stated earnings base
- Sub-industry dispersion shown, not averaged away
- Sector-characteristic red flags named
- An actionable setup delivered — own / avoid / watch
