Results for “go”

Run the HyperFrames CLI to scaffold, author, lint, preview, render, and publish video compositions locally or on HeyGen Cloud, AWS Lambda, and Google Cloud Run.

Converts long-form markdown documents (specs, RFCs, reports, plans) into a single-file HTML page with sticky table of contents, scrollspy, search filter, code-copy buttons, and customizable design tokens.

Extract public web data via HasData APIs, including search engine results, structured data from ecommerce, travel, jobs, and local business platforms, with support for web scraping, pre-parsed APIs, and async jobs.

Build and publish production-quality Chrome extensions using Manifest V3 best practices, covering service workers, content scripts, side panels, and Chrome Web Store deployment.

Use when the user wants to clone or adapt a UI pattern from any website into gotcontext.ai, or asks to "build something like X", "make our nav look like Y", or "clone that component". Prefer aura.build Pro when available; without a Pro subscription, skip Aura and go straight to Phase 2.5 direct rebuild. Aura's clone is now NATIVE — paste a URL or drag a screenshot into aura.build and it generates React/Tailwind directly; the Anima/Chrome-extension flow is only a fallback for login-gated pages Aura can't fetch server-side.

Convert Markdown files to HTML similar to `marked.js`, `pandoc`, `gomarkdown/markdown`, or similar tools; or writing custom script to convert markdown to html and/or working on web template systems like `jekyll/jekyll`, `gohugoio/hugo`, or similar web templating systems that utilize markdown documents, converting them to html. Use when asked to "convert markdown to html", "transform md to html", "render markdown", "generate html from markdown", or when working with .md files and/or web a templating system that converts markdown to HTML output. Supports CLI and Node.js workflows with GFM, CommonMark, and standard Markdown flavors.

Extract paginated product listings from e-commerce category pages, search results, or keyword searches with filters like price, brand, rating, and stock status. Supports Amazon, eBay, Walmart, Shopify, WooCommerce, and Google Shopping.

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.

any input (code, docs, papers, images) → knowledge graph → clustered communities → HTML + JSON + audit report. Use when user asks any question about a codebase, project content, architecture, or file relationships — especially if graphify-out/ exists. Provides persistent graph with god nodes, community detection, and BFS/DFS query tools.

Detects all languages used on a webpage — both declared (html@lang, hreflang, nested lang=, meta content-language) and actually present in the body text using Google CLD3 WASM. Reconciles the two signal sets and flags mismatches for i18n audits, hreflang validation, and multilingual content verification.

You are an expert in Bolt.new by StackBlitz, the AI-powered full-stack development environment that runs entirely in the browser. You help developers go from idea to deployed app in minutes using natural language prompts — Bolt generates complete applications with frontend, backend, database, and deployment, all running in a WebContainer without local setup.

Expo framework for React Native. Managed and bare workflows, Expo Router, EAS Build/Submit/Update, config plugins, and Expo SDK modules. USE WHEN: user mentions "Expo", "expo-router", "EAS Build", "expo-cli", "app.json", "expo-config-plugin", "Expo Go" DO NOT USE FOR: bare React Native without Expo - use `react-native`; Flutter - use `flutter`

Shipley-methodology federal proposal outline and section drafter. USE WHEN the user asks to draft a proposal volume, build an outline from the proposal_instruction ↔ evaluation_factor traceability (UCF Section L/M or equivalent for non-UCF — FAR 16 task orders, FOPRs, BPA calls, OTAs, agency-specific formats), generate a compliance matrix, write win themes, draft an executive summary, propose FAB (Feature → Advantage → Benefit) chains, identify discriminators, or 'respond to this RFP'. Pulls requirements, evaluation factors, instructions, customer priorities, and pain points from the active Theseus workspace KG and produces an evidence-cited draft. Also ships govcon HTML render templates under assets/ — hand the rendered content off to the `huashu-design` skill for PPTX / PDF / animation export. Format-agnostic — never assumes UCF section labels are present. DO NOT USE FOR clause compliance auditing only (use compliance-auditor) or extracting new entities (use govcon-ontology + the Theseus pipeline).

Designs new software features and multi-component changes for the current repo into implementation-ready BDD specs via autonomous codebase research, then commits the design for review (runs to completion without mid-design questions). Scope covers new features, greenfield design, and multi-component changes. Not for hardware/physical-system design, out-of-repo questions, single-file refactors, or known-root-cause bugs (those go to direct edits or systematic-debugging).

React and Next.js performance optimization guidelines from Vercel Engineering. Use this skill when writing, reviewing, or refactoring React/Next.js code. Apply it proactively whenever working on React components, Next.js pages, API routes, data fetching (server or client), bundle size, rendering performance, re-renders, server actions, hydration, animations, or JavaScript optimizations. If the code involves React or Next.js, use this skill — even if performance isn't the stated goal, these patterns prevent issues before they arise.

Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, embed, or tools, (2) Want to build AI agents, chatbots, RAG systems, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, Google, etc.), streaming, tool calling, structured output, or embeddings, (4) Use React hooks like useChat or useCompletion. Triggers on: "AI SDK", "Vercel AI SDK", "generateText", "streamText", "add AI to my app", "build an agent", "tool calling", "structured output", "useChat".

Review a built frontend against its chosen direction, catch drift back to generic AI defaults, enforce state coverage, ethical patterns, UX heuristics, and polish, and check contrast with APCA (not the legacy WCAG ratio). Produces specific, prioritized fixes — never vibes-based feedback. Works with pasted screenshots or Playwright MCP automated capture. Load when the user asks to review a UI, audit a design, check if a frontend looks generic or vibecoded, evaluate visual quality or polish, says "review this UI", "is this design good", "audit my frontend", "does this feel like [product]", "design QA", or when frontend-design routes here. Sub-skill of frontend-design.

Set up, run, and contribute to TokHub (github.com/yaojingang/TokHub) — an open-source AI API relay monitoring, recommendation, and OpenAI-compatible gateway system with L1/L2/L3 channel health probing, usage metering, alerts, audit, and Docker self-hosting. Use when the user asks about TokHub, "AI API 中转站监控", cloning/running the Go + React monorepo (TOKHUB_ROLE, sqlc, TimescaleDB, NATS), the L1/L2/L3 probe algorithm, the OpenAI-compatible `/gateway/v1/*` endpoint, or contributing a PR to TokHub. Do not use for connecting a running agent to a live TokHub instance's own API (that is covered by the project's own bundled `agent-skills/tokhub` skill inside the TokHub repo, not this one).

Structured threat modeling skill using the PASTA framework (Process for Attack Simulation and Threat Analysis) combined with Adam Shostack's 4-question framework. Use this skill whenever the user asks to do threat modeling, security analysis, map the attack surface, identify threats, or review an application for security risks — even if they don't mention PASTA or a specific framework by name. Core activities: Component Mapping (architecture + data flows), Critical Assessment (business impact prioritization), and Logic Flaw Identification (attacker mindset on business logic). Produces: component map diagram (Mermaid), data flow diagram (Mermaid), attack tree (Mermaid), STRIDE threat table, prioritized risk register, and an actionable mitigation plan. Invoke proactively for any security review, architecture review, or "what could go wrong?" session.

Reconstruct a product flow, then audit how usable it is — whether it makes sense, where users get confused or stuck, whether the copy and instructions are clear, and where friction causes drop-off. Produces a prioritized, severity-weighted findings report. Works from three inputs: frontend code in a repo, a live running app driven via a browser, or a written flow / spec / screenshots. Use this skill whenever the user asks for a UX review, usability audit, "is this flow confusing", "does this signup/onboarding/checkout make sense", "why are people dropping off", "audit this form", "where's the friction", or hands over a flow and asks whether it's user-friendly. Trigger even on casual phrasings ("is my checkout any good?") — it imposes the structure ad-hoc UX opinions miss. Audits flow usability and friction; for visual polish and interface quality the impeccable audit/critique skills apply instead.

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.