{
  "slug": "precision-vs-recall",
  "term": "Precision vs recall",
  "tools": [
    "sherlock-ai",
    "auditagent"
  ],
  "definition": "Precision is valid findings divided by all findings reported; recall is known bugs found divided by all known bugs. A useful evaluation reports both.",
  "detail": [
    "Sherlock AI's controlled study reports 55 percent precision; Nethermind reports 30 percent average recall on real audits. Neither number alone tells you whether a tool is worth running; together they tell you how much triage a given amount of coverage costs."
  ],
  "page": "https://agentsast.com/glossary/precision-vs-recall/",
  "updated": "2026-09-13"
}