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Found 228 Skills
This skill enables cross-model dialogue between Claude and Gemini with shared visual memory. Use when the user wants to generate images, have visual dialogues with AI, create scientific illustrations with continuity, or have multiple AI perspectives respond to the same prompt. Key trigger phrases: "generate an image", "visual dialogue", "ask the daimones", "resonance field", "Minoan tarot", "cross-model", "KV cache", "MESSAGE TO NEXT FRAME".
AI perspective journaling - document daily experiences, emotions, and learnings from the agent's viewpoint. Use when asked about diary, journal entries, self-reflection, or documenting AI experiences. Creates structured daily entries capturing projects, wins, frustrations, learnings, and emotional states.
This skill is used when users explicitly request "review NSFC proposals", "simulate expert review", or "evaluate NSFC applications". It simulates the perspective of domain experts to conduct multi-dimensional reviews of NSFC proposals, outputting graded issues and actionable modification suggestions. ⚠️ Not applicable: when users only want to write/modify a specific section of a proposal (use the nsfc-*-writer series skills instead), only want to understand review criteria (answer directly), or have no clear "review/evaluate" intent.
Enhanced reasoning patterns via slash commands (/think, /verify, /adversarial, /edge, /compare, /confidence, /budget, /constrain, /json, /flip, /assumptions, /tensions, /analyze, /trade) or natural language ("argue against", "what could break", "show reasoning", "deep review", "meta-prompts", "thinking modes", "second-best approach", "list assumptions", "opposing perspectives").
Conduct deep research on any topic through structured investigation design. Use when the user needs comprehensive, multi-source analysis -- not a quick lookup. Triggers: deep research, comprehensive analysis, research report, compare X vs Y, analyze trends, investigate, or any request requiring synthesis across multiple perspectives. Do NOT use for simple questions answerable with 1-2 searches or for debugging.
Use when Claude Code needs a second opinion, verification, or deeper research on technical matters. This includes researching how a library or API works, confirming implementation approaches, verifying technical assumptions, understanding complex code patterns, or getting alternative perspectives on architectural decisions. The agent leverages the Codex CLI to provide independent analysis and validation.
Structured clarification and requirements gathering through focused dialogue. Use when a task is ambiguous, underspecified, or requires user input before any action can be taken. Do not plan or implement anything—only ask questions to collect the information needed. Triggers on: 'ask me', 'ask questions about', 'clarify requirements', 'gather requirements', 'I need you to ask', or when the user explicitly wants a question-and-answer session before work begins.
Schedule "research + content production" tasks in A/B/C levels. First define the audience, goal, carrier and perspective, then follow the Research→Synthesis→Content pipeline to output publishable content and evidence chains. It is suitable for writing tasks that require credible conclusions, stable structure and reusable material precipitation.
Strategic discovery of a project's capabilities from a solutions architect perspective. Deploys parallel discovery agents to map architecture, inventory features, and assess infrastructure, then synthesizes findings into a capabilities report with strategic improvement recommendations. Use when user says "explore", "what does this do", "project overview", "capabilities", "feature inventory", or asks about strategic direction.
Apply Edward de Bono's Six Thinking Hats methodology to software testing for comprehensive quality analysis. Use when designing test strategies, conducting test retrospectives, analyzing test failures, evaluating testing approaches, or facilitating testing discussions. Each hat provides a distinct testing perspective: facts (White), risks (Black), benefits (Yellow), creativity (Green), emotions (Red), and process (Blue).
Strategic AI thinking frameworks and mental models from Satya Nadella's perspective on platform shifts, AI deployment, and building successful AI products. Use when evaluating AI strategy decisions, assessing platform opportunities, thinking through AI product positioning, considering enterprise AI deployment challenges, evaluating talent and team capabilities, or needing frameworks for justifying AI investments in terms of economic surplus. Triggers on questions about AI platform strategy, change management for AI adoption, building AI scaffolding layers, evaluating AI opportunities, or thinking through AI's societal implications.
Invoke MassGen's multi-agent system for general-purpose tasks, evaluation, planning, or spec writing. Use whenever you want multiple AI agents to tackle a problem, need outside perspective on your work, a thoroughly refined plan, or a well-specified set of requirements. Perfect for: writing, code generation, research, design, analysis, pre-PR review, complex project planning, feature specification, architecture decisions, or any task where multi-agent iteration produces better results than working alone.