lbo-model

Build leveraged buyout models in Excel — sources & uses, debt schedule, cash sweep, exit multiple, IRR/MOIC sensitivity. Pairs with excel-author. Use for PE screening, sponsor-case valuation, or illustrative LBO in a pitch.

Quality

77%

Does it follow best practices?

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tessl review fix ./optional-skills/finance/lbo-model/SKILL.md

Quality

Content

55%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

Strong workflow structure with explicit checkpoints and validation, but it is verbose with some redundancy, uses placeholder/external paths that don't resolve, and lacks any actual bundled template or reference files despite pointing to them.

Suggestions

Bundle the standard template (examples/LBO_Model.xlsx) and resolve the recalc.py script path to a real, included file so the repeated references are loadable rather than placeholders.

Tighten redundancy: the COMMON ERRORS table, verification checklist, and per-section checkpoint guidance overlap heavily — consolidate the color/formatting rules into one block.

Replace the '/path/to/excel-author/scripts/recalc.py' placeholder with either an included script or a concrete, resolvable reference, and confirm the excel-author pairing is stated once rather than repeatedly.

Dimension	Reasoning	Score
Conciseness	The body is useful and domain-specific, but it is long (270+ lines) with repeated material — e.g., the color/formatting conventions and the verification checklist restate the COMMON ERRORS table, and some guidance restates Excel basics Claude already knows.	2 / 3
Actionability	Concrete patterns exist (formula color codes, sensitivity-table mixed-reference patterns, the recalc.py command), but no complete executable example model and references to scripts like /path/to/excel-author/scripts/recalc.py and examples/LBO_Model.xlsx are placeholder paths no reader could resolve verbatim.	2 / 3
Workflow Clarity	It gives a clear section-by-section sequence (template analysis → S&U → operating model → debt schedule → returns → sensitivity) with explicit user sign-off checkpoints after each section and a verification checklist with validation via recalc.py returning zero errors.	3 / 3
Progressive Disclosure	No bundle directories (references/, scripts/, assets/, examples/) exist, yet the body repeatedly points to external paths — excel-author/scripts/recalc.py, examples/LBO_Model.xlsx, native-mcp skill — none of which are present or loadable, so references are dangling rather than well-signaled one-level-deep pointers.	1 / 3
	Total	8 / 12 Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, well-crafted description: specific actions, natural trigger terms, explicit 'what' and 'when', and a clear niche that distinguishes it from sibling skills. Voice is third person throughout.

Dimension	Reasoning	Score
Specificity	The description lists multiple concrete actions — 'sources & uses, debt schedule, cash sweep, exit multiple, IRR/MOIC sensitivity' — naming the specific LBO model components and deliverables.	3 / 3
Completeness	It answers 'what' (builds LBO models with the listed components) and 'when' explicitly via 'Use for PE screening, sponsor-case valuation, or illustrative LBO in a pitch', a clear trigger clause.	3 / 3
Trigger Term Quality	Natural terms a user would say are well covered: 'leveraged buyout', 'LBO', 'PE screening', 'sponsor-case valuation', 'IRR/MOIC', with domain-appropriate variations rather than jargon.	3 / 3
Distinctiveness Conflict Risk	The LBO/PE niche is highly specific and pairs explicitly with excel-author, making it unlikely to trigger for general Excel or generic valuation skills.	3 / 3
	Total	12 / 12 Passed

Validation

81%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 13 / 16 Passed

Validation for skill structure

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning
metadata_field	'metadata' should map string keys to string values	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	13 / 16 Passed

Repository: NousResearch/hermes-agent
Path: optional-skills/finance/lbo-model/SKILL.md
Commit: 4c9628e

Reviewed: about 14 hours ago

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