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finance_lbo_model

Build a leveraged buyout model for a target company, including sources & uses, debt schedule, returns waterfall, sensitivity tables, and an investment-committee-ready summary memo.

Instructions

Build a leveraged buyout model for a target company. Outputs sources & uses, debt schedule, returns waterfall (IRR, MOIC), sensitivity tables, and an investment-committee-ready summary memo. Args: message: Free-text objective for the action. target_company (required): Target company name or ticker. entry_multiple: Entry EV/EBITDA multiple. leverage_ratio: Net debt / EBITDA at close. hold_period_years: Investment hold period (default 5 years).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageNo
target_companyNo
entry_multipleNo
leverage_ratioNo
hold_period_yearsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

The description explains what the tool outputs but does not disclose behavioral traits such as whether the model is persistent, whether it modifies any state, or if any authentication is needed. With no annotations, the description carries the full burden but is only partial.

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

Conciseness5/5

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

The description is concise, with a clear opening sentence followed by a bulleted list of parameters. Every sentence is informative, and the structure is front-loaded with the main purpose. No extraneous content.

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

Completeness3/5

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

The description lists outputs but does not explain how the model is used after creation, prerequisites for the target company, or how the tool integrates into a workflow. The contradiction regarding target_company being required versus optional in the schema reduces completeness. Given complexity and presence of an output schema, the description is adequate but has gaps.

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

Parameters4/5

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

The description provides meaningful explanations for each parameter in an Args section, compensating for the 0% schema description coverage. Each parameter is described with its role, though the 'message' parameter is vague ('Free-text objective'). Overall, it adds substantial value beyond the schema.

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

Purpose4/5

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

The description clearly states the tool builds an LBO model and lists specific outputs. However, it does not differentiate from the sibling tool 'finance_dcf_lbo_spreadsheet', which likely performs a similar function. The purpose is specific but lacks sibling distinction.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, nor does it provide context for when not to use the tool. The mention of target_company as required contradicts the schema, adding confusion.

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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