roi

roi is a command for Claude Code from jeremylongshore/tons-of-skills-marketplace. It costs 5 tokens per session (1,270 once invoked), scanned A, original, MIT.

A calculator for estimating the return on investment, or ROI, of an AI automation project. It compares current labour, error, and opportunity costs with implementation and running costs.

In plain words
What is it for?
Use it to estimate annual benefits, net benefits, ROI percentage, and payback time for an automation project.
Why use it?
It turns time savings, fewer errors, faster processing, and costs into a financial estimate. This helps explain whether an automation project could pay for itself.

Command for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the roi-calculator plugin — 1 command shipped together

Good fit Use it to estimate annual benefits, net benefits, ROI percentage, and payback time for an automation project.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/jeremylongshore/tons-of-skills-marketplace/roi
About the project

Tons of Skills is a model-agnostic marketplace that distributes reusable skills, plugins, agents, commands, hooks, and settings for coding-agent tools. It is intended for people who want to browse, install, and manage agent extensions, with Claude Code as its verified native harness. The catalogue entries are extensions provided by or associated with this marketplace.

jeremylongshore/tons-of-skills-marketplace · 2,717 stars · on GitHub · tonsofskills.com

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.

Clone the repo
git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace

Made for: Claude Code.

Or install roi-calculator, the plugin that ships this one along with the rest of its 1 command.

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 roi

README.md
[![agentmods](https://agentmods.dev/badge/commands/jeremylongshore/tons-of-skills-marketplace/roi/github.svg)](https://agentmods.dev/commands/jeremylongshore/tons-of-skills-marketplace/roi)
Your own site
<a href="https://agentmods.dev/commands/jeremylongshore/tons-of-skills-marketplace/roi"><img src="https://agentmods.dev/badge/commands/jeremylongshore/tons-of-skills-marketplace/roi/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 roi

Your own site · 80×15
<a href="https://agentmods.dev/commands/jeremylongshore/tons-of-skills-marketplace/roi"><img src="https://agentmods.dev/badge/commands/jeremylongshore/tons-of-skills-marketplace/roi.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 5 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,270 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 original No closer match found 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 $0.00005 $0.01270
Opus 5 $0.00003 $0.00635
Sonnet 5 $0.00001 $0.00254
Haiku 4.5 $0.00001 $0.00127

Measured 9d ago against content hash 90a5bc6c5de2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

roi 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 9d 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.

plugins/ai-agency/roi-calculator/commands/roi.md · 207 lines

How it starts

The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ROI Calculator

Calculate and present compelling ROI for AI automation projects.

ROI Calculation Framework

Current State Costs (Annual)

Labor Costs:
- Hours per week: [X]
- Hourly rate: $[X]
- Annual cost: Hours × Rate × 52 = $[X]

Error Costs:
- Error rate: [X]%
- Cost per error: $[X]
- Annual error cost: $[X]

Opportunity Costs:
- Lost revenue due to delays: $[X]
- Missed opportunities: $[X]

Total Annual Cost: $[X]

Automation Solution

Implementation Costs:
- Agency fees: $[X]
- Software licenses: $[X]/year
- Training: $[X]
- Total implementation: $[X]

Annual Operating Costs:
- Software licenses: $[X]
- API costs: $[X]
- Maintenance: $[X]
- Total annual operating: $[X]

ROI Calculation

Time Savings:
- Current time: [X] hours/week
- After automation: [X] hours/week
- Time saved: [X] hours/week
- Annual hours saved: [X] × 52 = [X]
- Value of time saved: [X] × $[rate] = $[X]

Quality Improvements:
- Error reduction: [X]%
- Annual error savings: $[X]

Speed Improvements:
- Faster processing: [X]%
- Additional capacity: $[X]

Total Annual Benefit: $[X]
Net Annual Benefit: $[X] - $[X] operating = $[X]

ROI: (Net Benefit / Implementation Cost) × 100 = [X]%
Payback Period: Implementation Cost / Net Annual Benefit = [X] months

ROI Presentation Template

# ROI Analysis: [Project Name]

## Executive Summary
By implementing [solution], [Company] will save **$X per year** with an ROI of **X%** and payback period of **X months**.

## Current State Analysis

### Time Investment
Currently, your team spends:
- **X hours per week** on [process]
- **X hours per year** total
- **$X per year** in labor costs (at $X/hour)

### Quality Issues
- **X% error rate** costing approximately **$X per error**
- **$X per year** in rework and corrections

### Opportunity Cost
- **X hours per week** that could be spent on higher-value work
- Estimated **$X in missed revenue** due to capacity constraints

**Total Current Annual Cost: $X**

## Proposed Solution

### Implementation
- Development: $X
- Integration: $X
- Training: $X
**Total Implementation: $X**

### Annual Operating Costs
- Software licenses: $X/year
- API usage: $X/year
- Maintenance: $X/year
**Total Annual Operating: $X/year**

## Expected Benefits

### Time Savings
- **Reduce process time by X%**
- **Save X hours per week**
- **$X value of time savings per year**

### Quality Improvements
- **Reduce errors by X%**
- **Save $X per year in error costs**

### Capacity Gains
- **Free up X% of team capacity**
- **Enable $X in additional revenue**

**Total Annual Benefit: $X**

## ROI Summary

| Metric | Value |
|--------|-------|
| Implementation Cost | $X |
| Annual Operating Cost | $X |
| Annual Benefit | $X |
| Net Annual Benefit | $X |
| **ROI** | **X%** |
| **Payback Period** | **X months** |
| **3-Year Value** | **$X** |

## Comparison: Do Nothing vs Automate

### Year 1
- Do Nothing: Lose $X in inefficiency
- Automate: Invest $X, gain $X → Net $X

### Year 2
- Do Nothing: Lose $X (cumulative $X)
- Automate: Gain $X (cumulative $X)

### Year 3
- Do Nothing: Lose $X (cumulative $X)
- Automate: Gain $X (cumulative $X)

**3-Year Difference: $X**

## Risk Mitigation
- Phased implementation reduces risk
- 30-day warranty included
- Ongoing support available
- Proven technology stack

## Next Steps
1. Approve project scope
2. Begin implementation (Week 1)
3. See first results (Week 8)
4. Full ROI realized (Month X)

Read the full file on GitHub · 207 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. 9d ago First seen · 207 lines · 5 tokens per session scan A 90a5bc6c5de2

Subscribe to this mod's changes

roi is a command published in the GitHub repository jeremylongshore/tons-of-skills-marketplace (2,717 stars, last pushed today), licensed MIT. It adds 5 tokens to every session and 1,270 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.