Earnings Preview Analyst
Turn pre-earnings uncertainty into a structured view of estimates, scenarios, and catalysts.
The skill asks for web searches for consensus data, earnings timing, and historical reactions, but does not define permission scope, sensitive-data handling, source verification, user confirmation, external effects, or rollback. No malicious or destructive behavior is evident, so a mid-range score is justified, with deductions for incomplete data-flow transparency and safety controls.
The workflow is internally coherent, with reasonably clear company/quarter inputs and a structured output. However, search dependencies are unspecified, and there is no handling for invalid inputs, missing data, conflicting estimates, uncertain dates, or failure feedback. No reproducible tests are included, so the static score is capped and reduced.
The skill clearly targets pre-earnings analysis, lists semantic triggers, provides sector-specific metrics, and defines expected sections. It does not specify non-fit cases, input formats, coverage boundaries, or Chinese-language behavior; its core web-search dependency may also be difficult to reach from mainland-China networks, warranting a deduction.
The skill has readable stepwise organization, an output checklist, and some limitation reminders. Repository context supplies an Apache-2.0 license, contribution process, and CI validation, but the skill itself lacks versioning, changelog, explicit maintenance ownership, installation/dependency notes, examples, and troubleshooting guidance.
The workflow covers consensus estimates, key metrics, scenarios, catalysts, and trading setup, so it can produce a useful preview draft. However, stock-price implications lack a defined valuation or probability method, and sources for whisper data and options-implied moves are unspecified. The result still requires substantial professional review; under static calibration it cannot exceed 7 and is reduced further.
The instruction to record estimate sources and dates, plus the historical-reaction search step, provides limited auditability. There are no committed examples, key-path tests, third-party execution records, or defined cross-validation procedure, so only a limited static score is warranted.
- The output depends on external web searches; verify the company, quarter, reporting time, consensus estimates, and historical reactions against dated sources.
- Scenario stock reactions, whisper numbers, and options-implied moves have no defined calculation method and should not be treated as investment advice or trading signals.
- Handling is unspecified for missing data, conflicting sources, unreachable pages, and non-standard reporting dates; Chinese-language users and mainland-China network reachability are also not explicitly covered.
What it does & when to use it
This skill prepares an equity-research view before a company reports quarterly earnings. It gathers the reporting context, consensus estimates, earnings timing, and prior-call commentary, then organizes company-specific financial and operating metrics. It builds bull, base, and bear cases with operational drivers and potential stock reactions. The output is a one-page earnings preview covering expectations, watch items, catalysts, and the trading setup.
Identifies the company and reporting quarter; uses web search to gather consensus revenue, EPS, and segment estimates; finds the earnings date and whether the release is pre-market or after-hours; reviews the prior-quarter earnings call for guidance and commentary; builds sector-specific financial and operating metric frameworks; creates bull, base, and bear scenarios with revenue, EPS, drivers, and stock reactions; lists three to five catalysts; and includes recent stock performance and the options-implied move.
- An equity-research analyst preparing a company-specific watch list before quarterly results.
- A portfolio manager comparing consensus, buy-side expectations, and possible stock reactions ahead of a report.
- A sell-side analyst drafting positioning notes and bull/base/bear cases before earnings.
- A trader incorporating historical earnings reactions and the options-implied move into a pre-release setup.
Pros & cons
- Provides an end-to-end pre-earnings workflow from expectation gathering through scenarios and trading setup.
- Includes sector-specific operating metrics for technology/SaaS, retail, industrials, financials, and healthcare.
- Explicitly calls for dated estimate sources, buy-side whisper numbers, historical reactions, and options-implied expectations.
- The skill does not provide a data vendor, connector, or automation script; web research and validation depend on the runtime environment.
- It does not prescribe a specific valuation model, forecasting methodology, or formula for stock-reaction estimates.
- The provided source does not document an independent test suite, so cross-platform and data-access performance is not evidenced.
How to install
The skill is located at plugins/vertical-plugins/equity-research/skills/earnings-preview/. The repository says to install through Cowork by opening Settings → Plugins → Add plugin and pasting https://github.com/anthropics/financial-services, then selecting the desired vertical. The documented Claude Code commands are: claude plugin marketplace add anthropics/financial-services, followed by claude plugin install equity-research@claude-for-financial-services. A standalone installation procedure for this skill is not documented in the source.
How to use
In a session where the skill is installed and available, use a trigger such as “earnings preview for [company]” or “what to watch for [company] earnings.” Other documented triggers include “pre-earnings,” “earnings setup,” and “preview Q[X] for [company].” The expected output includes the company, quarter, earnings timing, consensus estimates, ranked watch items, bull/base/bear scenarios, catalyst checklist, and trading setup.