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 limingrui679-design · Agent Tool · ★ 503
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is high-stakes-analytics-decision-lab safe to install? View the security audit →
High-Stakes Analytics & Decision Lab A platform-neutral, evidence-constrained Skill for moving from an ambiguous question to a defensible analysis—and only then, when justified, to action. What the Skill does This Skill turns an ambiguous, consequential question into a reproducible evidence product and, only when justified, a bounded decision product. It can start from a question alone or from uploaded row-level data. Instead of assuming the data are clean, the model is useful, or a recommendation must be produced, it makes each transition conditional on visible evidence. T
| Stars | 503 |
| Forks | 52 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 64.0787809711533/100 |
| Open Issues | 3 |
| Last Updated | 2026-09-07 |
| Created | 2026-07-29 |
| Platforms | python |
| Est. Tokens | ~20k |
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high-stakes-analytics-decision-lab is A platform-neutral analytical Skill that profiles messy data, selects case-adaptive methods, and produces source-backed visual reports for high-stakes decisions.. It is categorized as a Agent Tool with 503 GitHub stars.
high-stakes-analytics-decision-lab is primarily written in Python. It covers topics such as agent-skills, analytics, data-quality.
You can find installation instructions and usage details in the high-stakes-analytics-decision-lab GitHub repository at github.com/limingrui679-design/high-stakes-analytics-decision-lab. The project has 503 stars and 52 forks, indicating an active community.
high-stakes-analytics-decision-lab is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to high-stakes-analytics-decision-lab on Agent Skills Hub include Awesome-Agent-Skills-for-Empirical-Research, ai-text-detector, science-superpowers. 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: