Skip to content

Hunch — carldaws

Ruby control-flow helper that asks plain-English questions about text or app data via a System One model and returns probabilities, picks, or ordered ratings for use directly in code.

Stars
19
Language
Ruby
License
MIT
Published by
Community
Author
carldaws
Last verified
Oct 2026

About this project

Hunch lets you ask questions about text or application data and use the answers in your Ruby code. You can get a probability, choose between options, or rate something on a scale. Questions are written in plain English; answers come back as Ruby values. Hunch asks a System One model, such as TypeSafe's Jev, which answers with calibrated probabilities rather than text. It is also available for TypeScript as @carldaws/hunch. Point Hunch at a System One endpoint. Jev is available through OpenRouter:

Quoted from the project's README. Read the full README.

Highlights

  • chance returns 0 to 1, with possibly, likely, probably, and almost_certainly thresholds plus custom levels.
  • pick chooses among symbol or described options; rate returns a level with numeric position for ordered scales.
  • Hunch.decide asks several questions about the same data in one API call with per-question answers.
  • SystemOne backend speaks noul, choice, and score; Stub backend supplies answers and records calls for tests.

Watch out

Point Hunch at a System One endpoint; a missing key raises when you ask. Rescue Hunch::APIError for timeouts, rate limits, server errors, and bad answers. Auth, validation, and configuration errors are not APIErrors. Copy reviewed against the repository README on 2026-10-04, not from running it.

Questions about this entry

Short answers drawn from the linked project or page.

Other listings of this project

Forks and copies of this project in the directory. This entry is the canonical one.

1GitHub stars
Browser agent that takes one Jev decision per action on top of agent-browser and only calls an LLM when confidence drops, escalating instead of guessing, with values, origins and irreversible clicks all guarded in code.
Jev Demos & Experiments#community#awesomejev#catalog-import
4GitHub stars
A CLI and agent skill that asks plain-English questions across a repository, sends each in-scope chunk to the provider, returns scored source locations to investigate, and runs recurring review rules on diffs.
Jev Agents & MCP#community#jevbest#catalog-import
4GitHub stars
Python library that maps Jev's Choice, Score and Noul onto verbs like classify, score, check, where, extract, verify and rank, keeping data shape in and out, batching one request per distinct row and caching answers.
Jev Integrations & Adapters#community#jevbest#catalog-import

More Jev resources like this

19GitHub stars
Rails decision layer that evaluates noul, choice and score questions about app state in one Jev request, with per-question confidence floors that gate auto-action versus human review.
Jev Integrations & Adapters#community#jevbest#catalog-import
19GitHub stars
Ruby gem that models Jev as field predicates: feels and decide bind to model attributes with shared definitions, thresholds, confidence gates, batching, and test tapes.
Jev Integrations & Adapters#community#jevbest#catalog-import
69GitHub stars
Provider-neutral TypeScript runtime for System One decisions: write choice, noul, and score code once, then run it on TypeSafe Jev, local Reflex, any compatible /v1/systemone endpoint, or a custom provider.
Jev Integrations & Adapters#community#jevbest#catalog-import
38GitHub stars
File-first project notebook where many agents share context in .context/ files while Jev only judges the next step and records it as JSON.
Jev Integrations & Adapters#community#jevbest#catalog-import
41GitHub stars
Typed Python planner runtime that turns batched Jev action distributions into executable probability trees and graphs for finite decision tasks.
Jev Integrations & Adapters#community#jevbest#catalog-import
34GitHub stars
Self-hosted agent runtime that adds an optional Jev judgment layer to memory filtering, lesson dismissal, request classification, and skill selection, with inspectable context and execution.
Jev Integrations & Adapters#community#jevbest#catalog-import
Back to all resources

From the Jev community

Posts from builders shipping with Jev right now.

Follow @typesafeai