{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "amal-david-awesome-jev--flag-anomalous-fields-in-data-files",
 "repo": "Amal-David/awesome-jev",
 "repo_url": "https://github.com/Amal-David/awesome-jev",
 "repo_slug": "amal-david-awesome-jev",
 "title": "Flag anomalous fields in data files with a Jev-based CLI",
 "page_title": "How to flag anomalous fields in data files with a Jev-based CLI with Awesome Jev",
 "summary": "Find unusual values in selected fields of a data file and review them in local previews.",
 "who": "An analyst or data engineer checking a CSV or other supported file for odd values before using it.",
 "problem": "Manual review of many rows for anomalies is slow and misses patterns in selected fields.",
 "outcome": "A set of flagged anomalies in chosen fields, with local previews and cached assessments for review.",
 "steps": [
  "Open the jevotron repository at https://github.com/cmungall/jevotron and read its README to confirm which file formats it supports.",
  "Choose the file and the fields you want checked.",
  "Run the jevotron CLI as its README describes on your file and fields.",
  "Open the local previews and review each flagged value.",
  "Keep or discard each flag, and rerun the CLI to reuse cached assessments for unchanged values."
 ],
 "agent_prompt": "Use the jevotron repo (https://github.com/cmungall/jevotron) to flag anomalies in the fields <field-names> of the file <path-to-file>. Return the flagged values with their row references and any local preview paths. Verify that every flagged value matches a field you selected.",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "30 minutes",
 "basis": "readme",
 "caveat": "The README lists local previews and cached assessments but does not say whether field values are sent to Jev, so check before using sensitive data.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "python",
 "requirements": [
  "Access to Jev through TypeSafe, which the SDK and integration entries rely on",
  "Git and Python, since most picks in this list are Python or run from a repo",
  "Review of each project's permissions and data handling before running it, as the README asks"
 ],
 "risk": "sensitive",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.8,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/amal-david-awesome-jev/flag-anomalous-fields-in-data-files/",
 "md": "https://dedupedai.com/use-cases/amal-david-awesome-jev/flag-anomalous-fields-in-data-files/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/amal-david-awesome-jev--flag-anomalous-fields-in-data-files.json",
 "api_version": "v1"
}