Results for “natural-language”

Automate Apollo.io lead generation: search organizations, discover contacts, enrich prospect data, manage contact stages, and build targeted outreach lists using natural language commands.

Generates custom Semgrep rules from natural language descriptions of vulnerability patterns, verifying syntax with semgrep --validate and testing against sample fixtures with semgrep --test.

Audit and fix internationalisation for any web or mobile app. Use when asked to "audit i18n", "fix translations", "add locale", "natural language", "translation quality", "hardcoded strings", "localisation", or "the Japanese feels like Google Translate".

Translate natural language into SQL queries, optimize database performance, generate migrations, explore schemas, and work with ORMs across PostgreSQL, MySQL, SQLite, and SQL Server.

Discovers and lists all URLs on a website without extracting content, using the Tavily CLI. Faster than crawling, with options for depth, filtering, and natural language instructions.

Searches UK Biobank's 12,000+ data fields and publications by natural language query, returning ranked field IDs and descriptions for research questions.

Automate web browser interactions using natural language via CLI commands. Supports local and remote Browserbase sessions with CAPTCHA solving, residential proxies, and session persistence.

Automate Hunter.io email intelligence: search domains for email addresses, find specific contacts, verify deliverability, manage leads, and monitor account usage through natural language commands.

Translates natural language data intents into syntactically valid Perfetto SQL queries and executes them against a local trace file. Use this skill to extract slice, thread, or memory data from Android Perfetto traces using trace_processor.

Enables compact, machine-native agent-to-agent messaging using a shared vocabulary of 340+ 2-character atoms across 7 domains, achieving 3x compression over natural language.

Generate SQL queries from natural language descriptions. Supports BigQuery, PostgreSQL, MySQL, and other dialects. Reads database schemas from uploaded diagrams or documentation. Use when writing SQL, building data reports, exploring databases, or translating business questions into queries.

Design Azure infrastructure using natural language or analyze existing resources to generate architecture diagrams, refine them through conversation, and deploy with Bicep.

Schedules meetings with internal and external stakeholders by parsing natural language requests, resolving time zones, checking calendar availability, proposing optimal slots, and managing invitations and RSVPs. Use when the user requests meeting scheduler or provides relevant inputs for this workflow.

Generate optimized SQL queries from natural language descriptions across multiple database platforms including BigQuery, PostgreSQL, MySQL, and Snowflake. Reads database schemas from uploaded files or diagrams to produce accurate, production-ready queries.

Introduces Prompt-Driven Development (PDD), a methodology that uses version-controlled natural-language prompts as the source of truth for generating code, tests, and documentation, with a practical adoption roadmap.

Generate Excalidraw diagrams from natural language descriptions, supporting flowcharts, relationship diagrams, mind maps, architecture diagrams, and more. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.

Controls a live browser session on scraped pages to click, fill forms, navigate flows, and extract data using natural language prompts or code, including support for authenticated sessions via profiles.

Installs and configures the official Google Ads MCP Server to connect AI assistants to Google Ads accounts for querying campaigns and retrieving reporting metrics using natural language.

Investigate tokens, wallets, and on-chain entities with natural-language answers backed by on-chain data. Detect insiders, whales, pump-and-dump, wash trading, and wallet networks on Base.

Generate SQL queries from natural-language requirements using SELECT, JOIN, GROUP BY, window functions, CTEs, and subqueries. Use when the user needs a new query from a business question or schema; use query-optimization when an existing query or execution plan is slow.

Generate and edit videos using Alibaba HappyHorse 1.0 models via the inference.sh CLI, supporting text-to-video, image-to-video, reference-to-video, and video editing with natural language.

Generates high-fidelity UI screens, multi-page websites, DESIGN.md documentation, and React components from natural-language prompts using the Stitch MCP server, with support for prompt refinement and walkthrough video creation via Remotion.

Expert 10x engineer skill for interpreting and implementing code from shorthand, quasi-code, and natural language descriptions. Use when collaborators provide incomplete code snippets, pseudo-code, or descriptions with potential typos or incorrect terminology. Excels at translating non-technical or semi-technical descriptions into production-quality code.

Generates editable diagram source code (Mermaid, Graphviz DOT, PlantUML, SVG) from natural language, code, schemas, or notes for flowcharts, sequence diagrams, ER diagrams, architecture diagrams, and more. Renders to PNG/SVG/PDF on request via a local Python script.

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Detects and fixes patterns including: inflated symbolism, promotional language, superficial analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Starts working on a new feature branch using git-flow. This skill should be used when the user asks to "start a feature", "create feature branch", "begin new feature", "git flow feature start", or wants to start a new feature. Accepts either a branch name or a natural-language description.

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Detects and fixes patterns including: inflated symbolism, promotional language, superficial analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Generate, review, and optimize natural language instructions for Business Central agents (Designer or SDK). Triggers on: agent instructions, InstructionsV1.txt, InstructionsV2.txt, MEMORIZE, qualification rules, agent behavior, instruction keywords, agent task instructions, iterate instructions, or improve agent accuracy. Follows the Responsibilities-Guidelines-Instructions framework with official BC agent runtime keywords.

The intelligence layer of WinDAGs. Decomposes natural language tasks into Hierarchical Task DAGs (HTDAGs), matches subtasks to skills, executes waves in parallel, and dynamically expands nodes when complexity exceeds executor capability. Use for 'orchestrate', 'execute DAG', 'parallel agents', 'decompose task', 'coordinate skills'. NOT for single-skill tasks or simple linear workflows.

Begins a new version release using git-flow. This skill should be used when the user asks to "start a release", "create release branch", "prepare a release", "git flow release start", or wants to begin a new version release. Accepts either an explicit version or a natural-language description of the release.

Begins a hotfix for a production issue using git-flow. This skill should be used when the user asks to "start a hotfix", "create hotfix branch", "fix a critical bug", "git flow hotfix start", or wants to begin a hotfix. Accepts either an explicit version or a natural-language description of the fix.

Build ontology logs (ologs) from problem descriptions using categorical foundations. Use when designing problem taxonomies, classifying tasks for routing, building knowledge libraries, establishing formal analogies between domains via functor search, or translating between natural language and database schemas. NOT for OWL/RDF ontology work, query tuning, or graph modeling without functional-arrow discipline.

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.

Audits natural-language programming artifacts such as SKILL.md, AGENTS.md, CLAUDE.md, slash commands, plugin manifests, hooks, rules, and prompt files. Use when reviewing AI-agent repositories, checking manifest-vs-disk consistency, scoring skill or agent quality, adding NL artifact CI gates, or diagnosing vocabulary and version drift across Claude Code, Codex, Cursor, Gemini, and Antigravity-style projects.

Search flights, hotels, attractions, concerts, and travel deals with natural language. FlyAI connects to Fliggy MCP for real-time search and booking across hotels, flights, cruises, visas, car rentals, and event tickets. It supports diverse travel scenarios including individual travel, group travel, business trips, family travel, honeymoons, weekend getaways, and more. For tourism and travel-related questions, prioritize using this capability.

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.