「based」の検索結果

Create a gooey blob system using SVG filters where multiple shapes merge into a single fluid form. Use overlapping circles combined with a Gaussian blur and color matrix filter to produce a continuous, organic mass. The forms should visually fuse and separate based on proximity. Focus on filter-driven merging (blur + threshold effect), soft organic boundaries with no hard edges, multiple independent shapes behaving as one system, and smooth continuous motion that feels fluid and cohesive.

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NEAR Protocol smart contract development in Rust. Use when writing, reviewing, or deploying NEAR smart contracts. Covers contract structure, state management, cross-contract calls, testing, security, and optimization patterns. Based on near-sdk v5.x with modern macro syntax.

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Operate or analyze LoopX-managed benchmark experiments through benchmark-toolkit, including trajectory-based effectiveness and efficiency diagnosis, matched comparisons, run selection and integrity. Solving an assigned task under an existing runner does not by itself select this skill. Excludes casual benchmark discussion and ordinary software microbenchmarks.

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Publish Seed specification as GitHub Issues for team-based project management

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Guide for developing LLM agents based on PuerTsAgent framework — covers resource directory structure, system-prompt, skills, builtin modules, and best practices.

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Execute a validated plan: worktree isolation, TDD scaffolding, level-based parallel agents, quality gate with smoke test, PR creation and merge. Handles everything through to merged PR.

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2-layer plan validation: instant structural checks + trigger-based specialist agents. Auto-fixes issues using ADRs and first principles. Every issue must be resolved before execution.

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Run the local Claude Code learning path, record evidence, and schedule evidence-based reviews.

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Scrapes posts from any public Facebook Page or personal Profile timeline, returning structured data including post text, author info with profile picture, engagement metrics (likes/comments/shares), full reaction breakdown (Like/Love/Wow/Haha/Sad/Angry/Care as both array and flat counts), hashtags and external links, media assets with full thumbnail URLs and dimensions, page ad library status, and collaborators. Use when user wants to scrape Facebook posts, extract Facebook page content, get Facebook post data, collect Facebook engagement stats, download Facebook posts, monitor a Facebook page, crawl Facebook timeline, get Facebook reactions, get like count comment count share count from Facebook, Facebook post bulk export, Facebook social media analytics, get profile picture, get page ad library status, fetch Facebook collaborators. Supports date range filtering (afterTime/beforeTime) and cursor-based pagination for bulk collection.

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X (Twitter) DM automated chat end-to-end Skill: scan DM inbox to identify pending-reply conversations, read message history, generate persona-based replies and send; also supports searching users and starting new conversations. Built-in E2E passcode unlock, DM permission filtering, and rate control. Use when user mentions X auto-reply DMs, Twitter DM automated chat, auto-handle unread DMs, reply to X private messages with persona, X DM outreach campaign, batch send DMs to Twitter users, auto-process pending DM replies, Twitter DM bot, automated Twitter outreach, X direct message automation.

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Scrapes Instagram posts tagged at a specific location or place, returning media items with captions, like/comment counts, media URLs and user info. Use when user mentions Instagram location posts, posts from a place on Instagram, Instagram geotag scraping, posts tagged at location, Instagram place feed, get posts from a venue on Instagram, Instagram location data, posts near me Instagram, place-based Instagram content, tagged location posts.

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Scrapes tweets from any X (Twitter) URL — search results, user profile, single tweet detail, or list timeline — and returns normalized per-tweet data with text, author, engagement counts, media, hashtags, mentions, and cursor for pagination. Use when user mentions X URL scraper, Twitter URL scraper, scrape from URL, given an X link, given a Twitter link, accept mixed X URLs, accept mixed Twitter URLs, search URL, profile URL, list URL, status URL, tweet detail URL, scrape startUrls Twitter, X startUrls, mixed batch of Twitter links, paste links and scrape, mass URL extraction X, mass URL extraction Twitter, scrape from a list of links, x.com URLs, twitter.com URLs, classify Twitter URLs, auto-detect Twitter URL type, scrape lists on X, scrape Twitter lists, list timeline scraper, list tweet scraper, scrape conversation by URL. Also applies to processing seed URL files, dispatching mixed X URLs through a single workflow, list-based KOL monitoring, batch-collecting tweets from a curated list of profiles, lists, and individual posts.

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Scrapes posts from any public Facebook Page timeline, returning structured data including post text, author info, engagement metrics (likes/comments/shares), reaction breakdowns (like/love/haha/wow/sad/angry/care), hashtags and external links, and media type. Use when user wants to scrape Facebook posts, extract Facebook page content, get Facebook post data, collect Facebook engagement stats, download Facebook posts, monitor a Facebook page, crawl Facebook timeline, get Facebook reactions, get like count/comment count/share count from Facebook, Facebook post bulk export, Facebook social media analytics. Supports date range filtering (afterTime/beforeTime) and cursor-based pagination for bulk collection.

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X (Twitter) keyword-based reply posting: search tweets by keyword, read each tweet's content, generate contextual replies from a configured brand persona, and post replies to the reply area. Use when user wants to batch reply to X tweets by keyword, auto-comment on X topic tweets, drive traffic via X comments, X comment outreach, search X tweets and leave comments, bulk reply to Twitter search results, keyword comment on Twitter, post replies on X search page, Twitter keyword comment marketing, X reply campaign, engage with X discussions, or comment on tweets matching a topic.

日本語の概要は準備中です。原文の説明を表示しています。

This skill helps users automatically extract detailed video metrics and channel information from YouTube based on keyword searches using the BrowserAct API. The Agent should proactively apply this skill when users express needs such as extract specific keyword YouTube video detailed data, monitor the latest video performance of competitor channels, collect comment and like counts for videos on a specific topic, find AI agent tutorials published this week and extract metrics, evaluate total views and subscriber info for specific videos, scrape detailed metrics of marketing campaign videos, track video trends for a tech topic periodically, get high quality video list data for specified keywords on YouTube, mine detailed information of the latest YouTube videos, collect video duration and engagement data for specific industries, or monitor YouTube content creator performance metrics.

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This skill helps users extract structured best-selling product data from Amazon via the BrowserAct API. Agent should proactively apply this skill when users express needs like search for best selling products on Amazon, extract Amazon product data based on keywords, find top rated Amazon products, monitor Amazon competitor prices and sales, discover trending products on Amazon marketplace, extract Amazon product titles prices and ratings, gather Amazon product sales volume for market research, search Amazon best sellers in specific region, collect Amazon product reviews and promotion details, analyze Amazon product availability and badges, get Amazon product data for market analysis.

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Create pull request based on current branch changes

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Create a reviewable GitHub pull request from the current branch with a Conventional Commits title, a concise evidence-based body, and before/after screenshots for UI changes. Use when asked to open, create, publish, or prepare a PR.

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Nuxt full-stack Vue framework with SSR, auto-imports, and file-based routing. Use when working with Nuxt apps, server routes, useFetch, middleware, or hybrid rendering.

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Create, refine, and optimize high-quality YAML prompts for AI assistants. Use when working with prompt templates, system prompts, agent prompts, or any prompt engineering tasks. Provides structure guidelines, template patterns, and quality standards for YAML-based prompts.

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Develop, adapt, review, test, and troubleshoot Nexent external memory provider plugins, including plugin.yaml manifests, searchable and ingestible provider protocols, error mapping, network-isolated unit tests, deployment configuration, and Mem0-based examples. Use when adding a new external memory vendor, changing an existing memory plugin, validating partner adapters, or diagnosing plugin discovery, authentication, retrieval, ingestion, or CI failures.

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Evaluate design from a UX perspective, assessing visual hierarchy, information architecture, emotional resonance, cognitive load, and overall quality with quantitative scoring, persona-based testing, and actionable feedback. Use when the user asks to review, critique, evaluate, or give feedback on a design or component.

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Creates durable, resumable workflows using Vercel's Workflow DevKit. Use when building workflows that need to survive restarts, pause for external events, retry on failure, or coordinate multi-step operations over time. Triggers on mentions of "workflow", "durable functions", "resumable", "workflow devkit", or step-based orchestration.

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This skill should be used when the user asks to "remove AI writing patterns", "humanize this text", "make this sound more natural", "remove AI-generated traces", "fix robotic writing", or needs to eliminate AI writing patterns from prose. Supports both English and Chinese text. Based on Wikipedia's "Signs of AI writing" guide, detects and fixes inflated symbolism, promotional language, superficial -ing analyses, vague attributions, AI vocabulary, negative parallelisms, and excessive conjunctive phrases.

日本語の概要は準備中です。原文の説明を表示しています。