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Found 540 Skills
Router skill for LLMQuant investor-lens workflows. Use when the user wants an investor-style reasoning overlay grounded in LLMQuant Data evidence.
Crea o actualiza tareas técnicas (TK-XXX) asociadas a una historia de usuario existente. Activar cuando el usuario solicite planificar implementación, descomponer trabajo, definir alcance técnico, estructurar subtareas o documentar especificaciones técnicas sin generar código ni pruebas. Activar también — por defecto — cuando el usuario solo entregue una referencia a una historia (p. ej. «US-004», «planifica US-007», «tareas para esta historia») — en ese caso el propósito es proponer stubs agrupados por unidad de trabajo que cubran los escenarios (SC-XX) y consideren las reglas de negocio (BR-XX) de la US, sin redactar TKs completas.
Vercel AI Elements for workflow UI components. Use when building chat interfaces, displaying tool execution, showing reasoning/thinking, or creating job queues. Triggers on ai-elements, Queue, Confirmation, Tool, Reasoning, Shimmer, Loader, Message, Conversation, PromptInput.
Design and implement memory architectures for agent systems. Use when building agents that need to persist state across sessions, maintain entity consistency, or reason over structured knowledge.
Executes OpenAI Codex CLI for code analysis, refactoring, and automated editing. Activates when users mention codex commands, code review requests, or automated code transformations requiring advanced reasoning models.
Assigns confidence scores to agent outputs based on multiple factors including source quality, consistency, and reasoning depth. Produces calibrated confidence estimates. Activate on 'confidence score', 'how confident', 'certainty level', 'output confidence', 'reliability score'. NOT for validation (use dag-output-validator) or hallucination detection (use dag-hallucination-detector).
Use when creating or modifying classes, modules, or functions. Use when feeling pressure to add functionality to existing code. Use when class has multiple reasons to change.
Multi-Model Collaboration — Invoke gemini-agent and codex-agent for auxiliary analysis **Trigger Scenarios** (Proactive Use): - In-depth code analysis: algorithm understanding, performance bottleneck identification, architecture sorting - Large-scale exploration: 5+ files, module dependency tracking, call chain tracing - Complex reasoning: solution evaluation, logic verification, concurrent security analysis - Multi-perspective decision-making: requiring analysis from different angles before comprehensive judgment **Non-Trigger Scenarios**: - Simple modifications (clear changes in 1-2 files) - File searching (use Explore or Glob/Grep) - Read/write operations on known paths **Core Principle**: You are the decision-maker and executor, while external models are consultants.
A skill that equips you with real-time, source-grounded web search and content retrieval using the Exa API—optimized for balanced relevance and speed (type="auto") and full-text extraction for downstream reasoning, RAG, and code assistance. Powering agents with fast, high-quality web search by Exa.AI.
Anticipate and neutralize every reason customers say "no" before they say it. Combine Chris Voss's negotiation psychology with systematic sales methodology to turn objections into opportunities. Use when: **Before sales calls** to prepare responses to common pushback; **After losing deals** to document and learn from objections; **Product positioning** to address concerns in marketing copy; **Pricing conversations** to defend value against price resistance; **Team training** to create an obje...
Orchestrates comprehensive cognitive thinking patterns for complex problem-solving. Analyzes tasks to select optimal pattern(s) from foundational, reasoning, creative, metacognitive, specialized, and neurodivergent categories. Chains multiple patterns when needed and validates outputs before responding.
Logseq Datascript schema, built-in properties/classes, and :db/ident discovery for composing or reviewing Datascript queries about blocks/pages/tags/properties/classes. Use whenever editing or reviewing Datascript pull selectors or queries, or any code that adds/removes attributes in pull patterns, or touches property namespaces/identifiers, or requires reasoning about property value shapes/ref/cardinality in Logseq.