expansion-revenue-finder

expansion-revenue-finder is a skill for Claude Code, Codex from OneWave-AI/claude-skills. It costs 73 tokens per session (588 once invoked), scanned A, original, MIT.

A guide for finding ways to sell additional products or features to a company’s existing customers. It examines usage, missing capabilities, team growth, industry comparisons, and competitive pressure.

In plain words
What is it for?
Use it to analyze customer portfolios, identify upsell and cross-sell opportunities, score accounts, and create an account-by-account expansion playbook.
Why use it?
It helps account teams focus on expansion opportunities supported by customer data instead of guesswork. It ranks opportunities by potential revenue, effort, and likelihood of success.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: model in frontmatter.

Good fit Use it to analyze customer portfolios, identify upsell and cross-sell opportunities, score accounts, and create an account-by-account expansion playbook.

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Install with agentmods
npx agentmods add skills/onewave-ai/claude-skills/expansion-revenue-finder
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 OneWave-AI/claude-skills --skill expansion-revenue-finder
Clone the repo
git clone --depth 1 https://github.com/OneWave-AI/claude-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 expansion-revenue-finder

README.md
[![agentmods](https://agentmods.dev/badge/skills/onewave-ai/claude-skills/expansion-revenue-finder/github.svg)](https://agentmods.dev/skills/onewave-ai/claude-skills/expansion-revenue-finder)
Your own site
<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/expansion-revenue-finder"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/expansion-revenue-finder/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 expansion-revenue-finder

Your own site · 80×15
<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/expansion-revenue-finder"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/expansion-revenue-finder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 588 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00073 $0.00588
Opus 5 $0.00036 $0.00294
Sonnet 5 $0.00015 $0.00118
Haiku 4.5 $0.00007 $0.00059

Measured 9d ago against content hash c0fb648bdc05, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

expansion-revenue-finder 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.

expansion-revenue-finder/SKILL.md · 34 lines

How it starts

The opening of the file, as written. The whole thing — 34 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Expansion Revenue Finder

Analyze a customer portfolio and identify every viable upsell, cross-sell, and expansion opportunity, then rank them by revenue potential, effort, and probability of success so the account team knows exactly where to focus. Optimize for total portfolio expansion revenue, not individual deal wins. Ground every recommendation in data signals, not wishful thinking.

Contents

  • references/data-inputs.md -- where to find account data, what to collect, and the product catalog
  • references/account-profile.md -- per-account expansion profile and segment benchmarking
  • references/expansion-triggers.md -- seven trigger categories and the opportunity record template
  • references/scoring.md -- three-dimension scoring rubric, composite formula, and tier interpretation
  • references/playbook-template.md -- the full expansion-playbook.md output structure
  • references/rules-and-edge-cases.md -- behavioral rules and edge-case handling

Workflow

  1. Collect data. Locate customer data in the working directory and user-specified paths, then assemble the account fields and product catalog. See references/data-inputs.md. If no structured data exists, ask the user to describe their accounts and note reduced scoring confidence.

  2. Profile and benchmark each account. Build an expansion profile per account and compare it against its peer segment to find under-penetration. See references/account-profile.md. Without external benchmarks, use the portfolio's top quartile as the benchmark.

  3. Scan for triggers. Check every trigger category for each account. Record an opportunity only when a trigger fires AND a matching product/feature is available to sell. Capture each as a structured opportunity record. See references/expansion-triggers.md. Flag underutilization as a separate "activation opportunity," not an upsell.

  4. Score and tier. Rate each opportunity on revenue potential, effort, and likelihood (1-10 each), compute the composite, and assign a tier. See references/scoring.md.

Read the full file on GitHub · 34 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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 · 34 lines · 73 tokens per session scan A c0fb648bdc05

Subscribe to this mod's changes

expansion-revenue-finder is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 73 tokens to every session and 588 once invoked, about $0.0004 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.

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