by adlumal · Agent Tool · ★ 71
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pip install goalchainTaken from the project's README on GitHub. Check the security audit before running it.
Flagged: environment access. 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.
| Stars | 71 |
| Forks | 4 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 65/100 |
| Open Issues | 1 |
| Last Updated | 2024-12-02 |
| Created | 2024-05-20 |
| Platforms | python |
| Est. Tokens | ~24k |
GoalChain GoalChain is a simple but effective framework for enabling goal-orientated conversation flows for human-LLM and LLM-LLM interaction. Installation Getting started Let's import the , , and classes, which are the basis for the conversation flow. In this example we will create an AI assistant whose goal is to collect information from a customer about their desired product order.
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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.
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