Generate high-potential viral title candidates for content across WeChat public account articles, X/Twitter posts, YouTube videos, Bilibili videos, and similar content platforms. Use when the user needs headline/title ideation, batch title generation, platform-specific title adaptation, title-library reuse, title…
Route viral topic discovery across platform-specific account-growth skills. Use when the user asks for 起号选题, low-follower viral references, recent viral content, cross-platform topic mining, or does not specify whether to search WeChat, X, Bilibili, or YouTube.
Find low-follower viral Bilibili videos for account-growth topic selection. Use when the user asks for B站低粉爆款, Bilibili low-fan hits, 起号选题 from B站, niche Bilibili references, or videos ranked by UP主粉丝数, 播放, 点赞, 投币, 收藏, 分享, 评论, 弹幕, and 播放粉丝比.
Find WeChat public-account articles that break out above the account's average reads for account-growth topic selection. Use when the user asks to discover 公众号爆款, 微信低粉爆款, 平均阅读爆款, 起号选题, category-based WeChat hot articles, or article references filtered by monthreadavg rather than unstable followercount.
Find low-follower viral posts on X/Twitter for account-growth topic selection. Use when the user asks for X low-fan hits, Twitter low follower viral posts, 起号选题 from X, niche tweet inspiration, or viral posts ranked by author followers, views, bookmarks, likes, reposts, and replies.
Find recent viral YouTube videos for account-growth topic selection. Use when the user asks for YouTube 爆款, YouTube hot videos, 起号选题 from YouTube, niche video references, recent high-view videos, or videos ranked by views, likes, comments, freshness, and topic relevance without low-follower filtering.
Collect and research materials for X (Twitter) content creation using multi-round web search strategy. Use when user wants to gather trending topics, research subjects for X posts, or mentions "collect materials", "research topic", "find content for X", "x-collect". Performs 4-round deep research mimicking human…
Create viral X (Twitter) posts including short tweets, threads, and replies. Use when user wants to write X content, create posts, or mentions "create tweet", "write thread", "x-create", "写推文", "创作推文". Supports 5 post styles with customizable templates, plus a mandatory humanize pass to reduce AI-sounding phrasing.…
Score and filter topics for X content creation using weighted criteria. Use when user wants to evaluate collected materials, filter topics by score, or mentions "filter topics", "score materials", "x-filter", "选题筛选". Applies 10-point scoring system with customizable weights.
Publish tweets and threads to X (Twitter) draft using browser automation. Use when user wants to publish content to X, save to drafts, or mentions "publish to X", "post tweet", "x-publish", "发布推文". Supports short tweets and threads. NEVER auto-publish, always saves to draft.
Generate free images with Agnes Image 2.1 Flash through the Agnes API, including text-to-image, image-to-image, high-density visual prompts, URL results, and local downloads. Use when the user asks for 免费图片, 免费的图片模型, free image API, Agnes image, Agnes Image 2.1 Flash, free AI image generation, image-to-image via…
Call the free Agnes text model API for chat completions, streaming answers, coding help, tool-calling experiments, and OpenAI-compatible text generation. Use when the user asks for 免费文本, 免费的文本模型, free text API, Agnes text, Agnes-2.0-Flash, free LLM calls, or wants to use a free chat/completion model through an Agent…
Create free Agnes video generation tasks and retrieve video results through Agnes-Video-V2.0, including text-to-video, image-to-video, multi-image video, keyframe animation, async polling, and video download. Use when the user asks for 免费视频, 免费的视频模型, free video API, Agnes video, Agnes-Video-V2.0, text-to-video…
A guide for designing systems where several specialised AI agents share work. It covers dividing responsibilities, passing short task summaries, managing task stages, and checking results.
A Chinese-language guide for designing systems that show where information comes from, such as document question-answering or search-based answers. It covers inline source markers, keeping citations during rewrites, and making factual claims traceable.
Design guidance for managing the limited amount of text an AI can consider at once, called its context window. It covers summaries, delayed loading, persistent memory, and token budgets.
Injection defense is a set of rules for stopping untrusted text from taking control of an AI agent. Prompt injection is an attack where content such as a document or webpage contains instructions meant to override the agent’s rules.
Design guidance for giving an AI a persistent memory system. It covers storing, finding, using, changing, and deleting information such as user preferences and project knowledge.
Mobile adaptation is a set of response rules for AI used on phones and tablets. It adjusts answer length, structure, and formatting to fit smaller screens.
Persona design defines an AI’s core identity, role, limits, and relationship with the user. It answers what the AI is and how it should behave in a specific product or context.
A personality system is a set of switchable style layers for an AI, such as friendly or professional. It keeps the AI’s core role separate from its tone and interaction style.