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ElBruno.AI.Decisions

elbruno/ElBruno.AI.Decisions

One .NET API for classification, routing, scoring, and assessment with probabilities.

Classification & Routing0.57Runner-up: Infra / SDKs / IntegrationsQuestionnaire
Automated README summary

Automatically summarized from the README on 3 Nov 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

ElBruno.AI.Decisions is a .NET 10 SDK for developers who need classification, routing, rubric scoring, or proposition assessment. It returns probability distributions instead of generated text, backed by Microsoft Foundry, local Ollama models, or the native Jev SDK.

How it uses Jev

The README lists ElBruno.AI.Decisions.Jev as a native TypeSafe AI Jev SDK and IDecisionClient adapter, but does not describe which decisions Jev makes, what state it receives, or how results are used in code.

Primitives:choicescorenoul

Technique worth stealing

Expose decisions as typed probability distributions through one IDecisionClient interface, letting providers be swapped behind a single API.

Try it

Install the ElBruno.AI.Decisions.Jev NuGet package; the README gives no Jev-specific run instructions.

View on GitHub

Start using Jev: API key and your first request →

Model judgments from README excerpts

Project signals use repository metadata, an existing summary and the first 700 README characters, not the full project. “Not found” means not detected in that material; it does not establish absence. These are the original judgments with recorded models and dates, not source audits or run results.

Models & evaluation dates

Inclusion gate
jev-1.14.0
Project signals
jev-1.14.0
Category
jev-1.14.0
Pattern tags
jev-1.14.0

Evidence

These signals use repository metadata, an existing summary and at most 700 cleaned README characters. ≥ 0.60 means reported in that excerpt; ≤ 0.40 means not found there. The middle band is inconclusive. None is a source-code audit or a test result. The runnable-tool question excludes research experiments; the recommendation question asks for a learning shortlist, not a quality verdict.

  • Jev is core to the projectnot found in the excerpt0.07
  • Shows a System One patternnot found in the excerpt0.15
  • Describes handling uncertaintynot found in the excerpt0.03
  • Reports measured numbersnot found in the excerpt0.02
  • Is a runnable toolFound in material0.96
  • Top-10 learning shortlist signalnot found in the excerpt0.10
  • Is a replica of the modelnot found in the excerpt0.10
  • Solves a common problem (0–2)score on a 0–2 scale1.61 / 2
  • About JevFound in material0.98
Signals
Jev is core to the project0.07Shows a System One pattern0.15Describes handling uncertainty0.03Reports measured numbers0.02Is a runnable tool0.96Top-10 learning shortlist signal0.10Is a replica of the model0.1000.51Solves a common problem (0–2)1.61 / 2012

no-judgment band (0.40–0.60)

Design patterns
Questionnaire0.9400.51

no-judgment band (0.40–0.60)

The Jev model and date for each judgment stage are listed above. Card written by DeepSeek V4.1 Flash from the README on 3 Nov 2026.