LLMDB.APP PROMPT LIBRARY
Meticulously engineered prompt frameworks for GPT-4o, Claude 3.5 Sonnet, DeepSeek R1, and Gemini 1.5 Pro. Search, filter, copy, or execute live in our multi-model sandbox.
Audit GitHub Actions/Jenkins pipeline YAML for security misconfigurations and generate prioritized remediation steps aligned with OWASP guidelines.
Help research strategists detect emerging topics and forecast dominant research trends from recent arXiv publication data.
Aggregating support tickets, feature requests, and survey responses into a weighted roadmap prioritization matrix.
Drafting high-conversion technical SaaS case studies following the Star-Story-Solution framework.
Generate realistic synthetic datasets that preserve the statistical properties of original data without exposing personal information, useful for testing, sharing, and model development.
Automatically generate a structured, blame-free post-mortem report with 5 Whys analysis from production incident logs and metrics.
Analyze screenplays or novels to map emotional beats, pacing, and visual arcs for storytelling improvement.
Automatically transform a feed of competitor updates into a structured strategic brief for marketing and product teams.
Validating changes to prompt templates against a suite of expected outputs to prevent quality regressions
Generating statistically valid A/B test hypotheses from user behavior data and past experiment results to optimize conversion rates.
Translating technical documentation (e.g., API guides, README files) into multiple languages while preserving code blocks, formatting, and domain-specific terms.
Analyze customer feedback data to uncover sentiment trends, key themes, and emerging issues over the past quarter.