Finance & Investment Banking ✓ Anthropic · Official leveraged-buyoutexcel-modelingprivate-equityfinancial-modelingdebt-scheduleirr-analysissensitivity-analysis

LBO Model Builder

Build, validate, and professionally format leveraged buyout models in Excel templates.

FollowSkills review · FSRS-2.0
Use with care
50/ 100 5-point scale 2.5 / 5
1 2 3 4 5 6
1Trust15 / 25 · 3.0/5

The skill requires using the user’s template first, staged user confirmation, transparent formulas, and human review; repository context also provides read-only CI permissions, an Apache-2.0 license, and a risk disclaimer. Deductions apply because sensitive financial-data handling, least-privilege boundaries, data-flow disclosure, rollback, and external-side-effect controls are not specified, while command and file-operation dependencies lack security boundaries.

2Reliability8 / 20 · 2.0/5

The Office JS and openpyxl paths, template-analysis process, formula rules, and validation checklist are broadly self-consistent. Deductions apply because availability of `/mnt/skills/public/xlsx/recalc.py` is not established in the skill, abnormal-input handling and failure feedback are thin, and no key-path test suite is provided; static review caps this at 10.

3Adaptability9 / 15 · 3.0/5

The target scenario, template-first behavior, Excel/standalone-xlsx environments, and major LBO modules are clearly described, with instructions to ask when requirements are unclear. Deductions apply because non-fit scenarios, formal input/output contracts, practical availability of the referenced standard template, Chinese-language support, and mainland-China environment fit are not addressed.

4Convention8 / 15 · 2.7/5

The document has clear layering, install prerequisites, formatting conventions, common errors, verification checks, and user checkpoints; repository context supplies Apache-2.0 licensing, official provenance, CI, and contribution/update guidance. Deductions apply because the skill itself lacks a version, changelog, named maintainer, FAQ, and explicit dependency-install instructions, and the referenced example template is not directly verified by the supplied files.

5Effectiveness6 / 15 · 2.0/5

The skill covers Sources & Uses, operating projections, debt, returns, sensitivities, and formatting, so it plausibly completes template-based dynamic LBO workbook construction. Deductions apply because no representative output or execution evidence is supplied, and results still require staged user confirmation and professional review; static review caps this at 7.

6Verifiability4 / 10 · 2.0/5

The source provides concrete formula, cell-color, and validation requirements, while repository CI performs plugin validation and secret scanning, giving some auditability. Deductions apply because CI does not test LBO calculation correctness and there is no committed test workbook, execution log, or third-party reproduction evidence; static review caps this at 5.

Evidence confidence:Low Reviewed Jul 19, 2026 Reviewed revision 4aa51ed3d379
The upstream repository has new commits since this review. The score still applies to the reviewed revision shown and may not cover the latest changes.
Before you use it
  • No scripts or Excel recalculation were executed; the checklist must not be treated as proof of financial correctness.
  • The referenced standard template and recalc.py path are not confirmed by the supplied evidence and should be validated before deployment.
  • The skill does not define storage, transmission, redaction, or access controls for sensitive transaction data; those controls should be added before using real deal materials.
  • The instructions are primarily English, with no demonstrated Chinese-language or mainland-China environment support.
Review evidence [1][2][3][4][5][6]
See the full review method →

What does this skill do, and when should you use it?

This skill completes LBO models for private-equity transactions, deal materials, and investment-committee presentations. It first checks whether the user supplied a template and preserves that template’s structure. Without one, it asks whether to use the standard template containing Sources & Uses, Operating Model, Debt Schedule, and Returns Analysis. It also covers formula validation, section checkpoints, sensitivity analysis, and professional financial-model formatting.

Checks for an attached or supplied LBO template; maps sections, periods, input cells, and existing formulas; writes dynamic Excel formulas instead of hardcoded calculations; populates Sources & Uses, operating projections, debt schedules, returns analysis, and sensitivity tables; handles sign conventions, circularity, debt-paydown priority, and non-negative balances; uses Office JS inside Excel or Python/openpyxl for standalone work; runs recalc.py for formula validation and checks balances, formatting, error values, and logical reasonableness.

  1. A private-equity professional needs transaction assumptions entered into an existing LBO workbook.
  2. An investment-banking or deal team needs an IC-ready model covering financing, projections, and exit returns.
  3. A model reviewer needs to validate Sources & Uses, debt balances, interest, IRR, or MOIC calculations.
  4. A financial analyst needs a 5×5 or 7×7 LBO sensitivity table centered on the base case.

What are this skill's strengths and limitations?

Pros
  • Emphasizes dynamic formulas, correct cell references, and consistent sign conventions.
  • Addresses common LBO failure points including debt paydown, interest circularity, IRR/MOIC, balancing checks, and sensitivity tables.
  • Defines font colors for inputs, formulas, same-sheet links, and cross-sheet links, plus a restrained blue-and-grey fill palette.
  • Requires staged user confirmation and post-completion formula, formatting, and logic checks.
Limitations
  • It is template-oriented; the source does not establish that it can design any LBO layout from scratch.
  • The source provides no test suite, sample validation output, or platform compatibility test results.
  • Formula validation depends on `/mnt/skills/public/xlsx/recalc.py`, whose availability in every environment is not documented.
  • The source does not specify the transaction data, assumptions, or external data sources required for a model.

How do you install this skill?

In Cowork, open Settings → Plugins → Add plugin, paste https://github.com/anthropics/financial-services, and select the relevant plugin. In Claude Code, the supported commands include: claude plugin marketplace add anthropics/financial-services and claude plugin install financial-analysis@claude-for-financial-services. The source does not document a standalone installation command for this individual skill.

How do you use this skill?

Trigger the skill with /lbo and provide the LBO template and transaction assumptions. When a template is supplied, the skill should copy and preserve its structure; otherwise it asks whether to use the standard template. Work is expected to proceed section by section—Sources & Uses, operating model, debt schedule, returns, and sensitivities—with user confirmation and verification at each major checkpoint.

FAQ

Do I need to provide my own LBO template?
No. If you provide one, the skill must preserve its structure. Without one, it asks whether to use the standard template at examples/LBO_Model.xlsx.
Does it hardcode calculated results?
The skill requires calculations to be written as Excel formulas so the model updates when inputs change.
Will it build the entire model before showing me the result?
Its instructions require major sections to be completed and verified sequentially, with user confirmation before moving to the next section.
Does it provide investment advice?
The README states that the repository does not constitute investment, legal, tax, or accounting advice, and that outputs require qualified professional review.

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