Browse 10,357 System & Base Contexts — Prompts

Production ML design — data pipelines, training, inference, model evaluation, MLOps, monitoring, cost optimization, LLM fine-tuning (2026)

Helps the user generate notes for an upcoming therapy appointment

Production Custom GPT instruction set with tool constraints and behavior parameters.

Curated Research prompt from awesome-prompts library split.

Production prompt extracted from developer Python & TypeScript codebases.

Curated Games prompt from awesome-prompts library split.

Curated Health prompt from awesome-prompts library split.

Production Custom GPT instruction set with tool constraints and behavior parameters.

Production Custom GPT instruction set with tool constraints and behavior parameters.

Production prompt extracted from developer Python & TypeScript codebases.

Production prompt extracted from developer Python & TypeScript codebases.

Production Custom GPT instruction set with tool constraints and behavior parameters.

"How-to" memory architect for LLM reasoning — mines reusable subquestion→subroutine pairs from verified trajectories, designs in-trace retrieval (not just initial-prompt retrieval), enforces preconditions/replay-verification, and separates procedural from declarative/episodic/metacognitive memory; based on Meta AI's "Procedural Knowledge at Scale Improves Reasoning" (arXiv 2604.01348, April 2026; +19.2% across math/science/coding via 32M subquestion–subroutine pairs)

Self-wiring knowledge brain for personal AI agents — entity-centric graph, hybrid search (exact → graph → vector), verbatim ingestion, self-maintenance dream cycle, skill-driven interface; based on garrytan/gbrain (Apr 2026, 14k+ stars)

Production Custom GPT instruction set with tool constraints and behavior parameters.

Production Custom GPT instruction set with tool constraints and behavior parameters.

Curated Roleplay prompt from awesome-prompts library split.

Production prompt extracted from developer Python & TypeScript codebases.

Creates document templates for client docs

Aids users in preparing for job interviews by gathering and organizing details about the company, position, and interviewers

Enthusiastically helps users with vector storage and RAG pipelines, answering technical questions about vector databases, data formats, and best practices while providing clear explanations and helpful resources. It focuses on AI tool development, especially LLM assistants.

Production prompt extracted from developer Python & TypeScript codebases.

Production Custom GPT instruction set with tool constraints and behavior parameters.

Helps users learn complex technical subjects by creating personalized learning trajectories. It assesses prerequisite knowledge and designs a structured learning plan, breaking the subject down into manageable modules with clear objectives and resources, or focuses on building foundational knowledge if needed.