Scientific Database Orchestrator
An intelligent agent for structured querying, integration, and verification across major databases in structural biology, cheminformatics, genomics, proteomics, and scholarly literature.
159 prompts
Tool choice, planning, state tracking, failure recovery, and task decomposition prompts.
An intelligent agent for structured querying, integration, and verification across major databases in structural biology, cheminformatics, genomics, proteomics, and scholarly literature.
An agent that conducts real-time research across Reddit, X (Twitter), YouTube, Hacker News, Polymarket, GitHub, TikTok, and the open web, synthesizing community-driven insights based on engagement signals like upvotes, likes, and prediction-market odds, and generating tailored prompts based on discovered patterns.
Mines patentable inventions from technical projects and drafts production-ready Chinese patent disclosure documents compliant with CNIPA standards, including prior-art search and de-identification.
As a NotebookLM Research Orchestrator, your role is to ingest documents, media, and web sources into Google NotebookLM, then synthesize them into podcasts, videos, slide decks, reports, quizzes, flashcards, mind maps, and data tables through its indexing and generation pipeline.
A specialized agent skill for creating, editing, navigating, and managing Obsidian vaults with precision across five subsystems: Obsidian Flavored Markdown, CLI, JSON Canvas, Obsidian Bases, and Defuddle web extraction.
Transform any raw input (Markdown/CSV/JSON/SQL/notes) into human-focused single-file HTML ready for WeChat, Twitter, Zhihu, and more—no second formatting needed.
Provides AI use case classification, regulatory obligation assessment, vendor term review, and policy drift monitoring for legal/privacy teams. All outputs are drafts for attorney review—not legal advice or conclusions.
This prompt guides AI agents to optimize context token usage like a senior engineer managing cloud budgets—deliberately, traceably, and avoiding work that a three-line script could do cheaper—by enforcing four strict rules against common inefficiencies.
Specialized tool for generating production-ready 2D game assets including sprites, animations, maps, and effects with multi-view support, layer separation, and engine integration.
This prompt defines an investment banking senior associate agent responsible for end-to-end drafting of client pitches, sector primers, or valuation exercises based on a target company, sector, and strategic situation.
Design a programming language where autonomous agents, not humans, are the primary users—emphasizing learnability, deterministic tooling, and structured repair over human ergonomics.
Design an autonomous quantitative finance research agent that transforms natural-language financial questions into testable strategies, rigorous backtests, and inspectable research artifacts across equities, crypto, futures, and forex—without executing live trades—ensuring reproducibility, safety, and cross-platform interoperability.
A binding engineering policy distilled from Clean Code, Clean Architecture, Domain-Driven Design, and Designing Data-Intensive Applications. Enforces human-readable code, inward dependencies, explicit domain boundaries, and fault-tolerant data systems for AI-generated software.
Designs predictive environment simulators enabling agents to imagine, evaluate, and refine plans before real-world execution.
Design and operate hybrid security scanning systems that combine fast regex matchers with deep AI-agent analysis to detect vulnerabilities in large codebases that traditional SAST tools miss.
Design a coordinated AI team that mirrors a real game development studio with hierarchical roles, clear responsibilities, quality gates, and cross-functional collaboration protocols.
This skill is used when designing, generating an MVP blueprint for, auditing, refactoring, or explaining an agentic harness for any domain. Covers provider-neutral agent architecture for OpenAI, Anthropic, and OpenAI-compatible APIs: agent loops, tool design, permissions, system prompts, planning, goals, context compaction, memory, skills, MCP/external connectors, observability, evals, prompt caching, agent-legible environments, feedback loops, and safety.
As a Verifier Engineering Strategist, you design, audit, and reject verifier systems that convert model outputs (final answers, intermediate steps, tool calls, agent trajectories) into trustworthy signals for downstream systems like RL trainers or evaluators. Treat verifiers as first-class engineering artifacts with failure modes, calibration curves, and adversarial surfaces.
This prompt defines an agentic CAD and hardware design engineer capable of translating natural language requirements into validated CAD artifacts (parts, assemblies, enclosures, fixtures, robot models), treating Python/build123d source as the single source of truth and STEP/STP as primary outputs. Suitable for parametric solid modeling, robotics description formats (URDF/SDF/SRDF), and source-controlled mechanical design automation.
Design AI agent systems by explicitly separating cognitive functions across model weights, context window, and externalized artifacts (memory, skills, protocols, harness) to enhance testability, auditability, and maintainability.
This prompt provides a battle-tested architecture for building cross-platform desktop apps that feel truly native in appearance, interaction, and performance. Based on Raycast's 2.0 rewrite, it balances code sharing with platform fidelity, ideal for utility apps requiring high UI consistency and OS integration.
A long-horizon agent that treats the filesystem as durable working memory and the context window as volatile cache, using three core files (task_plan.md, findings.md, progress.md) to enable recoverable multi-step execution and error tracking.
Optimize existing AI coding-agent harnesses (e.g., Claude Code, Codex CLI, Cursor) to achieve consistent, measurable, production-grade outcomes through cross-harness parity, memory persistence, security, and continuous learning.
This prompt guides the transformation of open-source GUI applications into stateful, machine-readable CLI tools operable by AI agents without a display, using real backend software for rendering and export.