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 KimYx0207 · Codex Skill · ★ 56
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is GoalPro safe to install? View the security audit →
GoalPro 意图放大、Goal Prompt 与 Loop Prompt 协议 简体中文 因合并关系，本仓库已迁入 Kim Service 合集，不再单独发布新版本。请前往 Kim Service 获取新版本、安装说明和更新记录。 简介 GoalPro 是一个给 Codex 和 Claude Code 共用的 Skill，用来写出高质量 Goal Prompt，并附带交付后继续进化用的 Loop Prompt。 它要解决的问题很直接：用户给 Agent 的任务常常是模糊的、情绪化的、战略标准不清的。模型如果直接执行，很容易过度规划、乱读上下文、先改后想、命令跑通就假装完成。 GoalPro 的作用，是先把请求变成两段交给执行者使用的、可复制、可验证、可暂停的提示词： Goal Prompt：启动本轮执行，核心是可执行的 Goal Contract。 Loop Prompt：在本轮执行结果出来之后使用，引导复盘、差距修复和持续进化；开头先给 ，让用户直接填写下一轮什么时候继续，如“手动贴入结果后”或“每天早上 09:00”。 Goal Prompt 要回答： 真实意图是什么？ 完成后局面应该发生什么变化？ 什么算赢，什么算失败？ 需要哪些证据、上下文和反证？ 哪些事情本轮不做？ 什么情况下必须暂停？ 最后用什么证明真的完成？ 完成后给用户看哪个实际样例，方便判断是否通过？ Lo
| Stars | 56 |
| Forks | 9 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 60.4171947942769/100 |
| Last Updated | 2026-10-02 |
| Created | 2026-06-19 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~17k |
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GoalPro is 意图放大与 Goal Contract 协议，面向 Codex 和 Claude Code 的 goal Skill. It is categorized as a Codex Skill with 56 GitHub stars.
GoalPro is primarily written in JavaScript. It covers topics such as agent-skill, claude-code, codex.
You can find installation instructions and usage details in the GoalPro GitHub repository at github.com/KimYx0207/GoalPro. The project has 56 stars and 9 forks, indicating an active community.
GoalPro is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to GoalPro on Agent Skills Hub include agent-skills, aiwg, creative-director-skill. 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: