Prompt Engineering for Log Diagnosis — What Actually Works With Gemini
The article explores effective prompt engineering techniques for diagnosing Android log errors using Google's Gemini model. By assigning a specialist role, marking the key error line, and constraining response length, the author significantly improved diagnostic accuracy. These methods were implemented in the open-source tool HiyokoLogcat, which supports both English and Japanese prompts.
- ▪The author tested various prompt versions to improve Gemini's log diagnosis accuracy.
- ▪Marking the key error line with a '>>' symbol helped Gemini focus on the correct issue.
- ▪Using role assignment, target line marking, and response length constraints yielded the best results.
- ▪HiyokoLogcat is a free, open-source tool available on GitHub.
- ▪The system adjusts prompts based on the user interface language, supporting both English and Japanese.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3851832) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } hiyoyo Posted on May 2 Prompt Engineering for Log Diagnosis — What Actually Works With Gemini #ai #gemini #rust #tauri All tests run on an 8-year-old MacBook Air. "Analyze this log" produces a generic answer. "You are an Android specialist. Identify the root cause and the specific fix." produces something useful. Prompt design matters more than most people expect. Here's what I iterated through for HiyokoLogcat's diagnosis feature.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV Community.
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