Results for “e-e-a-t”

Model-trader version compatibility protocol: Embed version metadata in checkpoints, validate at load time. Trigger when: (1) training and live trading versions diverge, (2) models fail to load, (3) action interpretation issues.

Use this skill when users want to search, discover, browse, or find Alibaba Cloud (阿里云) agent skills. Triggers include: "find a skill for X", "search alicloud skills", "阿里云有什么 skill","阿里云", "搜索阿里云技能", "有没有管理 ECS/RDS/OSS 的 skill", "阿里云 skills 有哪些类目", "帮我找一个 skill", "browse alicloud skills", "list alicloud skill categories", "is there an alicloud skill that can...", "what alicloud skills are available", "XX Skill 的内容是什么", "我想了解阿里云 XX Skill 具体做什么","帮我安装阿里云 Skill","使用阿里云相关的skill", "阿里云 agent skill 市场", "搜一下阿里云的 skill", "建一个数据分析项目有没有相关 skill".

Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.

This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.

Optimizes SQL queries, designs database schemas, and troubleshoots performance issues using execution plan analysis, indexing strategies, and set-based operations.

Authorized reverse engineering of custom binary protocols, Protobuf/gRPC, WebSocket frames, and PCAP-driven protocol recovery with structured workflow and tooling.

Co-constructs defined end states from vague goals through AI-proposed, user-shaped dialogue, building a GoalContract when neither party has a clear end state.

Pays for external AI model calls (image generation, real-time X data, LLM second opinions) from a wallet using micropayments, without requiring API keys.

Cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Enables building and training quantum circuits with automatic differentiation, seamless integration with PyTorch/JAX/TensorFlow, and device-independent execution across simulators and quantum hardware (IBM, Amazon Braket, Google, Rigetti, IonQ, etc.). Use when working with quantum circuits, variational quantum algorithms (VQE, QAOA), quantum neural networks, hybrid quantum-classical models, molecular simulations, quantum chemistry calculations, or any quantum computing tasks requiring gradient-based optimization, hardware-agnostic programming, or quantum machine learning workflows.

ScepticAgent internal architecture reference. Use whenever the user asks how the extension works, wants to add a new AI provider, add a new highlight category, debug communication between components, understand the agent loop or streaming, or work with provider routing and the Gemini CORS proxy.

Route web-scraping work into the lightest workable Scrapling mode instead of defaulting to a browser. Use when the user needs HTML extraction, JS-rendered page retrieval, protected-target escalation, quick CLI scraping, agent-facing MCP access, or a larger crawl with Scrapling spiders. Triggers on: scrapling, scrape website, crawl site, adaptive scraping, selector drift, stealthy fetch, browser scraping, scrape to markdown, scrapling mcp, scrapling spider, research harvesting, literature scraping, paper metadata.

Author a HyperFrames slideshow — a presentation, pitch deck, or interactive deck with discrete slides, fragment reveals, branching, hotspot navigation, and built-in presenter mode with speaker notes; also converts an existing page into a deck. Output is a navigable deck, not a rendered MP4. If the user didn't explicitly ask for a slideshow, confirm before authoring. Unclear → /hyperframes.

Guide federal systems through the NIST Risk Management Framework (SP 800-37 Rev 2) to achieve an Authorization to Operate (ATO), covering categorization, control selection, assessment, and continuous monitoring.

Use to write the PNAS abstract — a single self-contained paragraph of ~250 words, quantified and accessible to a broad scientific audience. Distinguishes the abstract (what/how/found, for scientists) from the Significance Statement (why-it-matters, for everyone). Late-stage polish.

Finds, scores, and reaches high-value contacts through social graph analysis and warm path discovery, with channel-specific outreach drafting.

Orchestrator — author the flow-anchored logical domain model (entities, state machines, events/commands, read models, policies, logical contracts) from an approved user-flow map, running one domain-modeling framework per session, before UX variation work

Three-layer verification pipeline for AI output. Extracts verifiable claims, finds supporting or contradicting sources via web search, runs adversarial review for hallucination patterns, and produces a structured verification report with source links for human review.

Generate changelog entries and GitHub releases from git history. Categorizes commits into features, fixes, breaking changes, and docs. Supports conventional commits, PR-based grouping, and semantic versioning. Creates formatted CHANGELOG.md entries and GitHub releases.

Probe the forms on a page for validation gaps — missing required-field enforcement, no client-side validation, accepts malformed input, and absent error messaging. Reports per-field findings. Playwright MCP only, no signup.

Run GitHub's Spec-Driven Development (SDD) workflow via the `specify` CLI — install spec-kit, initialize a project for one of 30+ AI coding agents (Claude Code, Copilot, Gemini, Cursor, Codex, Qwen, opencode, Kiro, etc.), and drive the constitution → specify → plan → tasks → implement command pipeline. Use when the user wants to bootstrap a Spec-Driven Development project, install `specify-cli`, generate executable specs before code, or invoke the `/speckit.*` slash commands (`/speckit.constitution`, `/speckit.specify`, `/speckit.plan`, `/speckit.tasks`, `/speckit.implement`, `/speckit.clarify`, `/speckit.analyze`, `/speckit.checklist`). Triggers on: spec-kit, speckit, specify, specify init, spec-driven, spec driven development, SDD, /speckit, executable spec.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

Design DynamoDB table schemas, write queries, configure indexes, manage capacity, and troubleshoot performance issues using AWS CLI and boto3 examples.

Classify customer support tickets, emails, or chats by category and priority, draft responses, and document next steps.

Persistent cross-session memory management. Enables agents to remember user preferences, project conventions, and past decisions across different sessions using a structured MEMORY.md index and topic files.

Set update priorities for an article before running detailed audits. Reviews extracted content and proposes which update audits to focus on (claims-stale, product-features-missing, topic-gaps).

Trigger: tech stack, preferred tools, SvelteKit, Bun, Drizzle, Zero Sync, Better Auth, Vite. Scope: Project tooling preferences, framework selections. Boundary: Excludes application logic or visual styling guidelines.

Data analysis workflow from import through modeling and communication. Use when analyzing a dataset, exploring data, building a statistical model, selecting features, or communicating findings to stakeholders.

Container/presentational component split — "smart" containers connect to the store, fetch data, and orchestrate loading/error/empty states; "dumb" children just render props. Use when extracting data logic from views, introducing custom hooks, or reviewing `*Container` components.

Orchestrate autonomous AI development pipelines through your Kanban board, managing multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

Deploy and configure an OpenTAXII server to share and consume STIX-formatted cyber threat intelligence using the TAXII 2.1 protocol for automated indicator exchange between organizations.

Builds elaborate, multi-component claude.ai HTML artifacts using React, Tailwind CSS, and shadcn/ui, with scripts to initialize and bundle projects into a single HTML file.

Migrates a Stitch screen to production React: fetches and caches wireframes, archives existing pages, converts to shadcn/ui components with semantic tokens, and documents the design system layers.

Research a topic and grow your knowledge graph. Uses Exa deep researcher, web search, or basic search to investigate topics, files results with full provenance, and chains to processing pipeline. Triggers on "/learn", "/learn [topic]", "research this", "find out about".

Use when user flows already exist and the team needs a screen inventory, screen responsibilities, key states, and view hierarchy for a product or feature. Trigger on requests to break a flow into pages, views, or screen-level structure.

Use DuckDB from MATLAB via Database Toolbox (R2026a+) as a non-math operations engine on large tabular files (CSV/Parquet/JSON) and as a zero-config embedded database. Use when connecting to DuckDB, querying CSV, Parquet, and JSON files directly with SQL, reducing or profiling large data before MATLAB analysis, creating portable development databases, or installing DuckDB extensions. Triggers on: DuckDB, duckdb(), large CSV/Parquet/JSON, file too large for readtable, filter/aggregate at source, deduplicate, reduce before analysis, profile large file, persistent file import, analytical engine, SQL on CSV, SQL on Parquet, SQL on JSON, query CSV with SQL, query Parquet with SQL, run SQL on files, SQL queries on files, query files directly, SQL without database, in-process SQL.

Knowledge-graph-augmented retrieval. Entity and triple extraction, graph construction (Neo4j, LlamaIndex PropertyGraphIndex), hierarchical community summarization (Microsoft GraphRAG), personalized PageRank (HippoRAG), multi-hop traversal retrieval, and hybrid graph + vector pipelines. USE WHEN: user mentions "GraphRAG", "HippoRAG", "knowledge graph RAG", "entity extraction", "multi-hop reasoning", "Neo4j RAG", "LlamaIndex property graph", "LangChain graph retriever", "triple extraction", "community summarization" DO NOT USE FOR: vanilla vector RAG - use `rag-patterns`; multimodal inputs - use `multimodal-rag`; production indexing ops - use `rag-production`; hallucination checks - use `rag-guardrails`