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lbo-model

Build a complete LBO model with sources & uses, operating projections, debt schedule, cash sweep, and sensitivity tables. Analyze IRR and MOIC for leveraged buyouts.

Instructions

Full LBO model: sources & uses, year-by-year operating model, debt schedule with cash sweep, IRR and MOIC, plus 3×3 entry/exit sensitivity tables. Pure computation — no API dependency. Priced $4.50, 10% below the closest x402 competitor at $5.00, with richer output including full operating model and dual sensitivity tables.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entry_ebitdaNoLTM EBITDA at acquisition (USD).
entry_multipleNoEntry EV/EBITDA multiple.
debt_multipleNoInitial leverage: Term Loan = entry_ebitda × debt_multiple.
cash_on_handNoTarget cash acquired at close (USD). Reduces equity check. Default 0.
existing_debtNoTarget existing debt refinanced at close (USD). Default 0.
transaction_fee_pctNoTotal transaction fees as % of purchase price (e.g. 0.04 = 4%). Default 0.04.
hold_yearsNoInvestment hold period in years (1–10).
entry_revenueNoLTM revenue at acquisition (USD).
revenue_growth_ratesNoAnnual revenue growth rate for each hold year (e.g. [0.08,0.07,0.06,0.05,0.05]).
ebitda_marginsNoEBITDA margin for each hold year (e.g. [0.25,0.26,0.27,0.27,0.27]).
exit_multipleNoExit EV/EBITDA multiple at end of hold period.
cash_sweep_pctNoFraction of FCF applied to optional debt repayment (0–1). Default 1.0.
interest_rateNoAnnual interest rate on term loan (e.g. 0.08). Default 0.08.
da_pctNoD&A as % of revenue. Default 0.04.
capex_pctNoCapEx as % of revenue. Default 0.03.
tax_rateNoEffective tax rate. Default 0.25.
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden. It discloses that the tool is 'Pure computation — no API dependency,' which is a key behavioral trait. However, it does not mention error handling, idempotency, or any side effects, leaving gaps in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two sentences. The first sentence efficiently conveys the tool's capabilities. The second includes pricing and competitor comparison, which is somewhat extraneous but not overly verbose. Overall, it is structured well.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (16 parameters, no output schema), the description covers high-level outputs (IRR/MOIC, sensitivity tables) and the computation-only nature. It lacks specifics on return format or error scenarios but provides a solid overview for an agent to understand the tool's result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning to the parameters beyond what the schema already provides. It lists the model outputs but does not elaborate on how parameters map to those outputs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as a full LBO model, listing specific components like sources & uses, operating model, debt schedule, IRR/MOIC, and sensitivity tables. It distinguishes itself from sibling tools by stating 'Pure computation — no API dependency.' The purpose is unambiguous and well-defined.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for LBO modeling but does not provide explicit guidance on when to use this tool versus alternatives. It mentions pricing and a competitor but lacks clear when-to-use or when-not-to-use instructions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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