{
 "schema_version": 1,
 "generated": "2026-10-23",
 "id": "appitstudio-awesome-jev--choose-decision-pattern-for-uncertain-results",
 "repo": "AppitStudio/awesome-jev",
 "repo_url": "https://github.com/AppitStudio/awesome-jev",
 "repo_slug": "appitstudio-awesome-jev",
 "title": "Pick Choice, Score, or Noul for an uncertain task",
 "page_title": "How to pick Choice, Score, or Noul for an uncertain task with Awesome Jev",
 "summary": "Match a decision task to the right Jev primitive and define what happens when the result is unsure.",
 "who": "A builder designing an automated decision who has to decide whether the output should be a choice, a score, or a Noul answer.",
 "problem": "Using the wrong Jev decision primitive, or ignoring uncertain results, can make an automated step act on weak answers.",
 "outcome": "A written decision pattern for your task, with a rule for handling uncertain results before the code acts on them.",
 "steps": [
  "Read docs/decision-patterns.md in the repo.",
  "List the decisions your workflow makes and mark each one as a choice, a score, or a yes-or-no judgment.",
  "Match each decision to Choice, Score, or Noul.",
  "Write a rule for what the workflow does when an answer is uncertain.",
  "Test the rule with one uncertain example before wiring it into live code."
 ],
 "agent_prompt": "Using docs/decision-patterns.md in the AppitStudio/awesome-jev repo, map the decisions in <my workflow> to Choice, Score, or Noul. Output a table with one uncertain-result rule per decision. Verify that every row names exactly one primitive.",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "15 minutes",
 "basis": "readme",
 "caveat": "The pattern guide describes how to match tasks to primitives; it does not measure how accurate Jev is for your data.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "python",
 "requirements": [
  "Node.js 22 or later, for installing the Awesome Jev Guide skill",
  "A coding agent such as Claude Code or Codex",
  "Python, if you want to use the TypeSafe Python SDK",
  "A TypeSafe API key, only for live calls; the offline examples need no account or key"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.7,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/appitstudio-awesome-jev/choose-decision-pattern-for-uncertain-results/",
 "md": "https://dedupedai.com/use-cases/appitstudio-awesome-jev/choose-decision-pattern-for-uncertain-results/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/appitstudio-awesome-jev--choose-decision-pattern-for-uncertain-results.json",
 "api_version": "v1"
}