No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by explorium-ai · Codex Skill · ★ 85
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is gtm-skills safe to install? View the security audit →
GTM Skills for Claude Code, Codex, Grok & AI Agents Open-source B2B data enrichment, prospecting, and outbound skills for Claude Code, Codex, Grok Build, Grok Bot, Hermes-Agent, OpenClaw, and Claude Cowork — powered by Explorium and Vibe Prospecting. These skills are ready-to-use playbooks that let any AI coding assistant run real GTM workflows: use as a prospecting skill to build prospect lists, an enrichment skill to enrich company and contact data, a lead scoring skill to tier leads, or a complete outbound skill for cold email and ABM campaigns — without custom tooling or agencies. Free to install, use, and adapt under the MIT license. Skills Build targeted B2B prospect lists from a natu
| Stars | 85 |
| Forks | 1 |
| Language | TypeScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 62.6477413082609/100 |
| Last Updated | 2026-09-24 |
| Created | 2026-06-01 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~18k |
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gtm-skills is GTM Skills for Claude & Codex. It is categorized as a Codex Skill with 85 GitHub stars.
gtm-skills is primarily written in TypeScript. It covers topics such as abm, account-research, ai-agents.
You can find installation instructions and usage details in the gtm-skills GitHub repository at github.com/explorium-ai/gtm-skills. The project has 85 stars and 1 forks, indicating an active community.
gtm-skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to gtm-skills on Agent Skills Hub include sales, gtm-eng-skills, gtm-engineer-playbook. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: