Results for “ai-q”

Applies cognitive science frameworks for creative thinking to CS and AI research ideation. Use when seeking genuinely novel research directions by leveraging combinatorial creativity, analogical reasoning, constraint manipulation, and other empirically grounded creative strategies.

Create and maintain Actor entities — humans and AI agents that participate in the project. Use when adding a new collaborator (human or agent) to the project, updating their preferences/expertise, or querying who does what.

Use when designing or building any user interface to ensure consistency, usability, and visual quality across all user-facing applications. This skill provides core UI/UX principles and standards for the enterprise ecosystem.

Run a broad SEO audit across technical SEO, on-page SEO, schema, sitemaps, content quality, AI search readiness, and GEO. Use as the umbrella skill when the user asks for a full SEO analysis or strategy.

CLI for Notion — authenticate, manage Workers, interact with the Notion API, and upload files. Use when an agent needs to create or query Notion pages, manage databases, upload files to Notion, or deploy Notion Workers.

Find current creator or editorial topics from AI Workstation Global Topic Radar and turn one into an evidence-backed content brief with research questions, must_verify, avoid_claims, and visual requirements.

Resolves an approved article comment task into a publishable AI markdown reply by fetching article context from a local HTTP API (with sf-cli fallback), reasoning with the selected quote and full article content, and writing the final reply to a backend-provided local result file path.

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

Transforms fuzzy problems into structured briefs that AI agents can reason about, critique, and act upon, while evaluating how much of the problem can be automated.

Evaluates the throughput and resource allocation efficiency of RIS-aided mobile edge computing systems by measuring the total computation task bits successfully completed under varying network conditions.

23 engineering agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw, and 6 more tools. Architecture, frontend, backend, QA, DevOps, security, AI/ML, data engineering, Playwright, Stripe, AWS, MS365. 30+ Python tools (stdlib-only).

WelineFramework SystemConfig scope configuration guide. Use when developing, reading, or changing module configuration, scope-aware settings, SystemConfig backend UI, PHTML config templates, w_query('system_config', ...), theme layout configuration entries, or website/store/global config behavior.

Expert guidance for Amazon Q Developer (formerly Fig), the terminal tool that provides IDE-style autocomplete, AI chat, and CLI builder capabilities. Helps developers create custom completion specs, build CLI tools with autocomplete, and configure terminal productivity features.

>- Advanced Product Quality Planning (APQP) — plan and track a new product launch through all 5 phases, identify deliverables per phase, run gate reviews, and ensure quality outputs are complete before Start of Production (SOP). Use when launching a new part, managing an APQP project, or auditing APQP completeness. Covers AIAG APQP 2nd edition and IATF 16949 §8.3.

Compose a provider-neutral AI team by tiering accessible models on cost-efficiency, capability, latency, and governance, then mapping the 8 processkit role archetypes onto catalog Roles + RoleSlots inside a chartering Scope. Use when bootstrapping a new project team, rotating after a provider change, or quarterly rebalancing. Triggers: "create my AI team", "compose a team", "rebalance the team", "review the team".

Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality

Query NFT and token data, trade NFTs on Seaport, swap ERC20 tokens via DEX aggregator, configure wallet signing providers, and build/register/gate AI agent tools on Base.

Review AI agent skills using a dual-axis method: deterministic code-based checks and LLM deep review, with weighted scoring and improvement recommendations.

Query NFT and token data, trade NFTs on Seaport, swap ERC20 tokens via DEX aggregator, configure wallet signing providers, and build/register/gate AI agent tools on Base.

Elite code review expert specializing in modern AI-powered code analysis, security vulnerabilities, performance optimization, and production reliability. Masters static analysis tools, security scanning, and configuration review with 2024/2025 best practices. Use PROACTIVELY for code quality assurance.

Expert knowledge for Azure AI Bot Service development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Azure AI bots with Direct Line/Web Chat, Teams, OAuth/SSO, human handoff, or proactive messaging, and other Azure AI Bot Service related development tasks. Not for Azure Health Bot (use azure-health-bot), Azure Functions (use azure-functions), Azure App Service (use azure-app-service), Azure Logic Apps (use azure-logic-apps).

Query the Yana AI codebase knowledge graph via codebase-memory-mcp. Use instead of grep/glob when exploring call chains, finding callers/callees, understanding architecture, or tracing impact of changes. Triggers on: 'who calls X', 'trace path', 'find callers', 'search graph', 'cbm', 'knowledge graph', 'what calls', 'call chain', 'what uses', 'where is X defined', 'architecture overview', 'impact of changing'.

Monta o roteiro da audiencia de instrucao e julgamento — AIJ (CPC 358-368): ordem das provas orais (361 — perito/assistentes, depoimento das partes, testemunhas do autor e do reu), inquiricao de testemunhas (perguntas pelas partes — 459), depoimento pessoal (385-388), pena de confesso, contradita, e as alegacoes finais orais (364) com prazo de 20 minutos. Use quando o operador disser audiencia de instrucao, AIJ, instrucao e julgamento, oitiva de testemunhas, perguntas para a testemunha, depoimento pessoal, alegacoes finais orais, ou houver AIJ designada para preparar.

Reference for querying the Atlas knowledge graph through its MCP tools — the SECONDARY enrichment/comparison layer that adds best-practice context to systems you have ALREADY scanned from your real sources (`az`, repos, dirs). Use when you need to look up nodes, edges, kinds, clusters, stats, or wiki pages in Atlas to compare against your real inventory. (atlas graph, query atlas, atlas mcp, search the graph, graph neighbors, atlas record, atlas kinds, enrichment layer)

Run multiple AI agents against a product, SDK, or docs site to score setup friction, speed, efficiency, error recovery, and doc quality from a minimal prompt.

Connects AI coding agents to the IOTA blockchain with tools for wallet management, Move smart contract development, and on-chain data queries via JSON-RPC and GraphQL.

Monitors Drata compliance posture by querying the Drata public API for control status, evidence collection, personnel compliance, and asset inventory, then produces a structured audit-readiness report.

Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.

Unified LLM Gateway - One API for 70+ AI models. Route to GPT, Claude, Gemini, Qwen, Deepseek, Grok and more with a single API key. Use when: the user needs model routing, provider setup, or Chinese LLM access guidance.

Manage biological datasets and models with LaminDB, an open-source lineage-native lakehouse. Covers setup, artifact registration, query/search, lineage tracking, validation, ontology-backed annotation, collections, branches, storage, and workflow integrations.

The learner teaches the concept to the AI, which plays a curious novice peer and identifies gaps through authentic questions. Use when the learner wants to test their understanding — teaching forces a different kind of organisation than studying.

RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows, Office, NeMo. RWKV-7 (March 2025). Models up to 14B parameters.

Generate brand-quality product images by selecting a photography mode and answering a short interview; the backend enhances the prompt and submits it to GPT Image 2.

Integrate with Benchling's Python SDK and REST API to manage registry entities, inventory, ELN entries, workflows, and Data Warehouse queries for life sciences R&D automation.

Runs comprehensive SEO audits and analysis for websites, covering technical SEO, content quality, schema markup, Core Web Vitals, local SEO, and AI search optimization using browser automation tools.

Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. For systems venues (OSDI, NSDI, ASPLOS, SOSP), use systems-paper-writing instead.