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.
Synthesizes scattered multi-source competitive signals into a structured intelligence brief with confidence scores, strategic implications, and watch-list actions for product and GTM leaders.
Ingest a legacy monolith's repo structure, manifests, and code samples to produce a risk-scored, phased modernization roadmap with strangler-fig strategies and rollback checkpoints.
Audit a design system's token palette and component states for WCAG 2.2 and APCA contrast compliance, then generate corrected tokens and annotated specs for designers and developers.
Converts a repository's commit history into a structured, timestamped video tutorial script with voiceover narration and visual production cues.
Automating pull request reviews to provide developers with contextual, actionable feedback and code suggestions.
Turn a raw CSV/JSON dataset into a publication-ready scrollytelling data story with narrative prose, chart specs, and runnable D3.js/Plotly code.
Generate ranked, accessibility-compliant UI/UX A/B test variations with predicted performance metrics from behavioral data and current UI inputs.
Continuously monitor competitor public channels, extract strategic moves, rank alerts by relevance and impact, and deliver structured BI-ready intelligence briefs with recommended actions.
HR and L&D teams can generate tailored upskilling plans for employees that align individual career growth with organizational skill needs.
Enrich AI-generated apps and demos with real, cited web data to replace hallucinated facts and strengthen research-backed output.
Helps developers classify their own prompting habits and choose the best strategy for a given coding task.
Predict and score security vulnerabilities in CI/CD pipeline changes before deployment, with prioritized fixes and deployment recommendations.