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.
npx skills add OneWave-AI/claude-skills --skill expansion-revenue-findergit clone --depth 1 https://github.com/OneWave-AI/claude-skillsWrote 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.
[](https://agentmods.dev/skills/onewave-ai/claude-skills/expansion-revenue-finder)<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.
<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>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once 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 |
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.
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 catalogreferences/account-profile.md-- per-account expansion profile and segment benchmarkingreferences/expansion-triggers.md-- seven trigger categories and the opportunity record templatereferences/scoring.md-- three-dimension scoring rubric, composite formula, and tier interpretationreferences/playbook-template.md-- the fullexpansion-playbook.mdoutput structurereferences/rules-and-edge-cases.md-- behavioral rules and edge-case handling
Workflow
-
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. -
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. -
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. -
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.
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.
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.
- 9d ago First seen · 34 lines · 73 tokens per session scan A c0fb648bdc05
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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