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 AnotiaWang · Agent Tool · ★ 606
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-decision-models safe to install? View the security audit →
Awesome Decision Models A curated list of decision models (also called System One models or typed decision models) and the APIs, runtimes, tools, applications, benchmarks, and research around them. English | 简体中文 · Website A decision model reads a state (text, JSON, and for some models images) plus questions whose answers you declare up front, and returns a probability for every answer instead of generated text. Questions come in three shapes: Noul (the probability that a statement is true), Choice (one of your options), and Score (a level on an ordered rubric). TypeSafe AI introduced the category in September 2026 with Jev and its API, and many of the models and runtimes below accept the same request shape. Community-maintained and not affiliated with any model provider. Pull requests welcome. Contents Hosted APIs Open Models Inference Techniques Runtimes & Platforms SDKs & Clients Applications Demos & Games Agent Tools Benchmarks & Evaluations Papers Articles Related Contribute Hosted APIs API-only
| Stars | 606 |
| Forks | 124 |
| Language | Python |
| Category | Agent Tool |
| License | CC0-1.0 |
| Quality Score | 59.4959968965857/100 |
| Open Issues | 5 |
| Last Updated | 2026-10-02 |
| Created | 2026-09-17 |
| Platforms | python |
| Est. Tokens | ~25k |
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awesome-decision-models is A curated list of decision models (System One / typed decision models): hosted APIs, open-weight models, runtimes, SDKs, applications, benchmarks, and papers.. It is categorized as a Agent Tool with 606 GitHub stars.
awesome-decision-models is primarily written in Python. It covers topics such as ai-agents, awesome, awesome-list.
You can find installation instructions and usage details in the awesome-decision-models GitHub repository at github.com/AnotiaWang/awesome-decision-models. The project has 606 stars and 124 forks, indicating an active community.
awesome-decision-models is released under the CC0-1.0 license, making it free to use and modify according to the license terms.
The top alternatives to awesome-decision-models on Agent Skills Hub include awesome-jev-gallery, awesome-typesafe-jev, awesome-jev-typesafe. 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: