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 lookalike-customer-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/lookalike-customer-finder)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/lookalike-customer-finder"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/lookalike-customer-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/lookalike-customer-finder"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/lookalike-customer-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 | $0.00054 | $0.00392 |
| Opus 5 | $0.00027 | $0.00196 |
| Sonnet 5 | $0.00011 | $0.00078 |
| Haiku 4.5 | $0.00005 | $0.00039 |
Grade A, and why
lookalike-customer-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.
What it actually says
Lookalike Customer Finder
Analyze a company's best customers and find similar companies that match the same profile, producing a high-quality, ranked target account list.
Contents
references/scoring-model.md- Profile dimensions, weighted scoring model, and score bands.references/output-template.md- Full Markdown report structure (ICP, ranked lookalikes, market insights, targeting strategy, action plan).references/data-sources.md- Recommended enrichment tools and data points to gather.references/examples.md- Best practices, trigger phrases, and an example request.
Workflow
- Collect the best customers provided. If none are given, ask for the top 5-10 accounts.
- Analyze common characteristics across them. See
references/scoring-model.mdfor the five profile dimensions. - Build the Ideal Customer Profile (ICP) from those shared traits.
- Search the market for companies matching the ICP. Pull firmographics, tech stack, growth signals, and contacts from the tools in
references/data-sources.md. - Score each candidate 0-100 using the weighted scoring model in
references/scoring-model.md. - Rank and tier the companies by score (Tier 1: top 10, Tier 2: next 40, Tier 3: next 50).
- Produce the report following
references/output-template.md, including market insights, a tiered targeting strategy, and a quick-start action plan. - Apply the best practices in
references/examples.mdthroughout: favor quality over quantity, weight growth signals, and enrich contacts before recommending outreach.
What ships with it
4 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 · 27 lines · 54 tokens per session scan A 78be82dbaff6
lookalike-customer-finder is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 54 tokens to every session and 392 once invoked, about $0.0003 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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