Anonymous M&A Teaser
Create a one-page anonymous profile that tests buyer interest before NDA execution in a sell-side M&A process.
The skill requires anonymization, client and legal review, and restrictions on cities, customers, brands, and identifiable imagery, which reduces disclosure risk. However, it does not define input handling, storage, or outbound data boundaries; it does not require explicit confirmation before generation or distribution; and recipient tracking creates an external-process effect. The Apache-2.0 license and verified official publisher support attribution, but rollback and data-flow controls are absent, so points are deducted.
The workflow, required inputs, document structure, and output section are internally consistent and make the happy path understandable. There are no dependency notes, templates, validation scripts, abnormal-input handling, or diagnosable failure messages, and the mechanics for producing DOCX, PDF, or PowerPoint files are unspecified. The score therefore remains modest under static-only calibration.
The audience, sell-side M&A scenario, trigger phrases, anonymization requirements, and expected outputs are clear. Non-fit scenarios, missing-input behavior, language support, and mainland-China environment fit are not addressed, and boundaries for different transaction sizes or regulatory contexts are limited. These omissions reduce the score.
The document uses a readable progressive workflow covering inputs, structure, checks, and outputs. Repository context supplies an Apache-2.0 license, plugin-validation CI, and contribution/update guidance. The skill itself lacks versioning, changelog, named maintenance responsibility, install dependencies, worked examples, FAQs, and detailed limitation disclosure, so full marks are not justified.
The skill can guide creation of a one-page anonymous M&A teaser with core business, financial, and transaction information, while emphasizing accurate language and human review. However, there is no reusable template, verified representative output, or specified file-generation mechanism; producing DOCX/PDF may still require substantial manual work. The static cap and these gaps justify the score.
The skill file is auditable, and the repository includes generic plugin-validation and secret-scanning CI. It provides no skill-specific test suite, representative output, third-party execution evidence, or cross-source corroboration. The assessment therefore relies mainly on one normative document and receives limited verifiability.
- Before generation or distribution, confirm the anonymization scope, sensitive-data handling, recipient scope, and legal-review status.
- Actual DOCX, PDF, and PowerPoint generation is not defined in the skill; manually verify pagination, formatting, anonymization, and financial figures.
- Do not treat claims such as “leading” or “high-growth” as facts without support; stop for missing data or inadequate anonymization and request human judgment.
What does this skill do, and when should you use it?
Teaser is designed for sell-side M&A processes where advisors need to introduce a target company without disclosing its identity before an NDA is signed. It organizes business, industry, financial, geographic, selling-point, disclosure, and buyer-audience inputs into a concise marketing document. The output covers a deal code name, sector descriptor, anonymous company description, investment highlights, financial summary, and transaction overview. It also includes an anonymization review and calls for client and legal review before distribution.
Collects the company's business model, sector, revenue, EBITDA, growth rate, margins, geographic footprint, key selling points, anonymization boundaries, and target buyer type; drafts an anonymous company description, investment highlights, financial summary, and transaction overview in a one-page format; checks for potentially identifying company names, brands, products, cities, customers, partners, distinctive employee counts, overly precise financial figures, and identifiable imagery; and specifies Word, PDF, and optional single-slide PowerPoint deliverables.
- A sell-side advisor needs a blind marketing document for initial buyer outreach before an NDA is signed.
- An investment banking team has company metrics and transaction highlights and needs them organized into a one-page buyer-screening document.
- A deal team wants a concise transaction overview suitable for both strategic and financial buyers.
- A process lead needs an anonymity check before distributing preliminary materials.
What are this skill's strengths and limitations?
- Provides a clear workflow from input gathering through anonymization review.
- Includes a practical one-page structure and financial metrics table.
- Covers common buyer concerns including positioning, revenue quality, growth, margins, management, and strategic value.
- Explicitly requires client and legal review and recommends tracking recipients.
- The skill provides no sector-specific templates, data connectors, or automation scripts.
- The source does not show tested implementations for generating Word, PDF, or PowerPoint files.
- Users must supply accurate deal information and make disclosure judgments.
- Its scope is limited to anonymous one-page teasers; it does not cover full CIMs, valuation models, or buyer lists.
How do you install this skill?
In Cowork, open Settings → Plugins → Add plugin, paste https://github.com/anthropics/financial-services, and select the investment-banking vertical. In Claude Code, add the marketplace and install the vertical with: claude plugin marketplace add anthropics/financial-services; claude plugin install investment-banking@claude-for-financial-services.
How do you use this skill?
Provide the company's business and revenue model, sector, revenue, EBITDA, growth rate, margins, geographic footprint, 3–5 selling points, information to anonymize or disclose, and whether the audience is strategic buyers, financial buyers, or both. Then use a trigger such as: “Draft a blind teaser for a sell-side process.” The source does not specify a particular upload method or an automated export implementation.