returns-analysis

returns-analysis is a skill for Claude Code, Codex from w95/awesome-claude-corporate-skills. It costs 0 tokens per session (857 once invoked), scanned A, a copy of returns-analysis, MIT.

A private-equity deal calculator that estimates investment returns such as IRR and MOIC under different assumptions. Private equity is investing in companies, while IRR measures an annualised return and MOIC compares money received with money invested.

In plain words
What is it for?
Use it to build a base-case return estimate and sensitivity tables for entry and exit multiples, leverage, growth and holding periods.
Why use it?
It helps show how changes in purchase price, borrowing, company growth, sale price or holding period affect a deal’s outcome.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to build a base-case return estimate and sensitivity tables for entry and exit multiples, leverage, growth and holding periods.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/w95/awesome-claude-corporate-skills/returns-analysis
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add w95/awesome-claude-corporate-skills --skill returns-analysis
Clone the repo
git clone --depth 1 https://github.com/w95/awesome-claude-corporate-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for returns-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/w95/awesome-claude-corporate-skills/returns-analysis/github.svg)](https://agentmods.dev/skills/w95/awesome-claude-corporate-skills/returns-analysis)
Your own site
<a href="https://agentmods.dev/skills/w95/awesome-claude-corporate-skills/returns-analysis"><img src="https://agentmods.dev/badge/skills/w95/awesome-claude-corporate-skills/returns-analysis/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for returns-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/w95/awesome-claude-corporate-skills/returns-analysis"><img src="https://agentmods.dev/badge/skills/w95/awesome-claude-corporate-skills/returns-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 857 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 97% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.00857
Opus 5.5 $0.00000 $0.00343
Sonnet 5.5 $0.00000 $0.00171
Haiku 4.5 $0.00000 $0.00086

Measured 1mo ago against content hash 2c570932b588, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

returns-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

97% identical to returns-analysis — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

02-finance-accounting/returns-analysis/SKILL.md · 117 lines

How it starts

The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Returns Analysis

description: Build quick IRR/MOIC sensitivity tables for PE deal evaluation. Models returns across entry multiple, leverage, exit multiple, growth, and hold period scenarios. Use when sizing up a deal, stress-testing assumptions, or preparing IC returns exhibits. Triggers on "returns analysis", "IRR sensitivity", "MOIC table", "what's the return at", "model the returns", or "back of the envelope".

Workflow

Step 1: Gather Deal Inputs

Ask for (or extract from prior analysis):

Entry:

  • Entry EBITDA (LTM or NTM)
  • Entry multiple (EV / EBITDA)
  • Enterprise value
  • Net debt at close
  • Equity check size
  • Transaction fees & expenses

Financing:

  • Senior debt (x EBITDA, rate, amortization)
  • Subordinated debt / mezzanine (if any)
  • Total leverage at entry (x EBITDA)
  • Equity contribution

Operating Assumptions:

  • Revenue growth rate (annual)
  • EBITDA margin trajectory
  • Capex as % of revenue
  • Working capital changes
  • Debt paydown schedule

Exit:

  • Hold period (years)
  • Exit multiple (EV / EBITDA)
  • Exit EBITDA (calculated from growth assumptions)

Step 2: Base Case Returns

Calculate:

Metric Value
Entry EV
Equity invested
Exit EBITDA
Exit EV
Net debt at exit
Exit equity value
MOIC
IRR
Cash-on-cash

Show the returns waterfall:

  • EBITDA growth contribution
  • Multiple expansion/contraction contribution
  • Debt paydown contribution
  • Fee/expense drag

Step 3: Sensitivity Tables

Build 2-way sensitivity matrices:

Entry Multiple vs. Exit Multiple

Exit 6x Exit 7x Exit 8x Exit 9x Exit 10x
Entry 7x
Entry 8x
Entry 9x
Entry 10x

EBITDA Growth vs. Exit Multiple (at fixed entry)

Leverage vs. Exit Multiple (at fixed entry and growth)

Hold Period vs. Exit Multiple

Show both IRR and MOIC in each cell (IRR / MOIC format).

Read the full file on GitHub · 117 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 117 lines · 0 tokens per session scan A 2c570932b588

Subscribe to this mod's changes

returns-analysis is a skill published in the GitHub repository w95/awesome-claude-corporate-skills (281 stars, last pushed 8mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 857 tokens. A static security scan graded it A with 0 findings. It is 97% identical to returns-analysis, differing in 7 lines, and is treated as a copy.

Related

Other skills, from other repositories

financial-expert

A financial research skill for China and Hong Kong securities, funds, company finances, economic indicators, research reports, announcements, news, and business-risk data. It returns data and neutral analysis rather than placing trades or recommending investments.

modelstudioai/skills · 98 tokens

stock-analysis-lead

Orchestrate a US-stock investment analysis — classify sector archetype, fetch SEC filings, dispatch a tiered fan-out of six vertical equity-research agents (business model, earnings quality, balance sheet, management, industry, peer comparison) over a validated JSON findings contract, then synthesize a buy/hold/sell…

johnqtcg/awesome-skills · 229 tokens

stock-business-review

Review a US-listed company's business model and revenue structure for an equity-research workup. Covers product/service mix, customer concentration, geographic exposure, industry position, revenue-growth decomposition (organic vs acquired vs price vs volume), and information-tier discipline (which numbers are facts vs…

johnqtcg/awesome-skills · 121 tokens

stock-earnings-quality-review

Review a US-listed company's earnings quality, cash-flow integrity, and operating leverage for an equity-research workup. Covers operating cash flow vs net income drift, free cash flow trajectory, capex character (maintenance vs expansion), equity issuance / shareholder-return yield, revenue-quality signals…

johnqtcg/awesome-skills · 147 tokens

stock-peer-comparison-review

Independently benchmark a US-listed target equity against 2-4 closest peers on a fixed 12-item ratio panel — growth rates, profitability, capital intensity, balance sheet leverage, capital returns, and valuation multiples. Provides cross-validation for moat and market-share claims made by the business and industry…

johnqtcg/awesome-skills · 127 tokens

stock-balance-sheet-review

Review a US-listed company's balance sheet health for an equity-research workup. Covers net-debt/EBITDA leverage, current ratio, cash runway, goodwill concentration and impairment history, DSO trend, inventory days, off-balance-sheet items (operating leases, contingent liabilities), and pension underfunding. Trigger…

johnqtcg/awesome-skills · 107 tokens