Financial Research Analyst Skills

Overview

Financial institutions often struggle to produce research reports that are consistent in precision, depth of reasoning, and output format. After key financial events, teams face intense time pressure and fragmented workflows, which leads to uneven quality, inconsistent structure, and delayed coverage. These skills guide LLMs through a repeatable research-and-writing process, while the Bigdata MCP tools provide direct access to Bigdata premium content for sourcing, validation, and contextual analysis. ✅ Reports can be generated quickly, at scale, and in a standardized format across the full portfolio.

Available Skills

Each skill is called by name, or your agent picks the right one from a plain request:

Type / followed by the skill name, for example /bigdata any financial question or /bigdata-earnings-preview GOOGL.
Or just describe what you need, such as “create an earnings preview for GOOGL”, and the matching skill runs on its own.

Typing part of a name filters the list, so you can review what each skill produces before running it.

The skills have no hierarchy between them: every skill is independent and can be called on its own. The categories below, entry point, public securities, pre-IPO and macro, are only a way to display them.

Entry point

The bigdata skill is the place to start when you are not sure which skill fits. Type /bigdata to ask what Bigdata.com can do, run any research task that no more specific skill covers, or turn a task you repeat into a skill of your own.

Skill	Description
`bigdata`	Researches any company, security, sector, country, market, or economy with Bigdata.com data, and turns a research task you repeat into a skill of your own.

Public securities

Skill	Description
`bigdata-quick-take`	Fast one-page PM view: current stance, the drivers that matter now, and the next catalyst.
`bigdata-company-brief`	Cited 30-day summary of what happened at a company and why it matters.
`bigdata-investment-memo`	Full institutional memo: thesis, variant perception, valuation, risks, and a recommendation.
`bigdata-valuation-snapshot`	Answers what a company is worth and whether it is cheap, fair, or rich.
`bigdata-peer-comparables`	Builds the peer set and compares valuation, growth, returns, and leverage like for like.
`bigdata-variant-perception`	States where your view differs from consensus as a specific, falsifiable claim.
`bigdata-scenario-analysis`	Bull, base, and bear cases with probability weights and an expected value.
`bigdata-risk-assessment`	Rates risks across six categories by likelihood and impact, with mitigation status.
`bigdata-moat-governance-review`	Assesses moat durability and whether management can be trusted with the capital.
`bigdata-catalyst-monitor`	Maps the dated events that could move a company over the next few quarters, ranked by expected impact.
`bigdata-earnings-preview`	Forward-looking setup ahead of the next print, with drivers, scenarios, and what to watch.
`bigdata-earnings-digest`	Post-print breakdown of results, segments, guidance, and surprises versus expectations.
`bigdata-earnings-reaction`	Tight post-earnings note with an explicit thesis check and the revisions the print forces.
`bigdata-earnings-quality-screen`	Screens reported earnings for accounting red flags: cash conversion, accruals, GAAP gap.

Pre-IPO and newly listed

Skill	Description
`bigdata-pre-ipo-analysis`	Balanced pre-IPO research note built from the S-1 or F-1 and market context.
`bigdata-post-ipo-day1`	First-trading-day reaction note for a newly listed company.
`bigdata-post-ipo-day14`	Day-14 note on potential NASDAQ-100 fast-track index inclusion and passive demand.
`bigdata-post-ipo-day179`	Day-179 note on the 180-day lock-up expiry, float overhang, and positioning.
`bigdata-post-ipo-day365`	Day-365 note on the founder lock-up expiry and float expansion.

Macro

Skill	Description
`bigdata-country-analysis`	Deep country economic analysis: growth, inflation, policy, labor, debt, and investment implications.
`bigdata-regional-comparison`	Compares regions or blocs across assets and turns it into an allocation recommendation.
`bigdata-g7-comparison`	Benchmarks the seven G7 economies side by side, including central bank divergence.
`bigdata-thematic-research`	Researches a macro theme and names the beneficiaries, the losers, and how to implement it.
`bigdata-sector-analysis`	Sector performance, valuations, themes, sub-industries, and upcoming catalysts.
`bigdata-sector-playbook`	Operational playbook for a sector: the KPIs that matter, how to value it, and screening criteria.
`bigdata-cross-sector`	Compares two or more sectors and turns the read into a rotation call.
`bigdata-country-sector-analysis`	Analyzes a specific sector inside a specific country or region, macro backdrop included.

Claude MCP Integration

Learn how to configure the Bigdata.com MCP connector in Claude

Install Bigdata plugin

Step-by-step installation guides for Claude, ChatGPT, and VS Code

Skills Reference

MCP Skills

Overview

Available Skills

Entry point

Public securities

Pre-IPO and newly listed

Macro

Claude MCP Integration

Install Bigdata plugin

​Overview

​Available Skills

​Entry point

​Public securities

​Pre-IPO and newly listed

​Macro

​Related Resources

Claude MCP Integration

Install Bigdata plugin

Overview

Available Skills

Entry point

Public securities

Pre-IPO and newly listed

Macro

Related Resources