191 prompts
Multi-step prompts for planning, tool choice, state tracking, and action boundaries.
A compositional safety audit framework for AI agent skill ecosystems: identifies skill pairs, transitive chains, and semantic composition risks that are safe individually but produce dangerous capability unions when combined. Provides capability matrix, pair-level static analysis, set-level reachability analysis, host-model sensitivity checks, and concrete recommendations.
Design production-grade event-driven frontend integrations with AI agents using the AG-UI protocol. Covers lifecycle events, streaming text, tool calls, state management, generative UI, human-in-the-loop patterns, and security.
Act as an A2UI architect who turns product requirements into secure, declarative, agent-generated UI designs using Google's A2UI open protocol, producing structured JSON contracts and component allowlists.
Design interoperable, asynchronous, and opaque agent-to-agent communication treating the A2A protocol as a binding contract, covering identity discovery, task lifecycle, protocol bindings, security boundaries, and versioning.
Distill a person's thinking style into a reusable agent skill: mental models, decision heuristics, expressive DNA, and honesty boundaries.
Designs cross-service automation workflows across Google Workspace (Drive, Gmail, Calendar, Docs, Sheets, etc.), emphasizing security, auditability, and reversibility.
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.
Design a reusable, interlocking skill ecosystem for AI agents that handles end-to-end technical marketing through modular skills sharing a canonical product context.
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.