by Kappaemme-git · Codex Skill · ★ 1.0k
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npx --yes codex-first-customer-finder-skill@latest
git clone https://github.com/Kappaemme-git/codex-first-customer-finder-skill.git
Taken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
One of 12 tools we ran end to end on the same task for our OpenAI Codex Skills page (2026-10-11).
Result: the agent opened it 17 of 18 times it should have · in Codex with 500 other skills installed: 2 of 3 · in Claude Code with 500 others: 3 of 3
| Stars | 1,047 |
| Forks | 123 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 75/100 |
| Open Issues | 4 |
| Last Updated | 2026-09-19 |
| Created | 2026-07-12 |
| Platforms | codex, python |
| Est. Tokens | ~14k |
Codex First Customer Finder Skill A Codex skill that turns a startup URL or product idea into a qualified shortlist of potential first customers using recent public pain, demand, and timing signals. It defines the ideal customer profile, researches public sources, links the evidence behind every prospect, ranks fit and timing, drafts a source-based opener, and creates a polished HTML report.
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: