dream-interpreter
AI 解梦大师。用户描述梦境,智能追问关键细节后,从三个视角(周公解梦/心理分析/赛博神棍)生成解读,输出结构化 JSON 供前端渲染"梦境解析卡"。
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
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AI 解梦大师。用户描述梦境,智能追问关键细节后,从三个视角(周公解梦/心理分析/赛博神棍)生成解读,输出结构化 JSON 供前端渲染"梦境解析卡"。
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
AI 新闻聚合与热度排序工具。当用户询问 AI 领域最新动态时触发,如:"今天有什么 AI 新闻?""总结一下这周的 AI 动态""最近有什么火的 AI 产品?""AI 圈最近在讨论什么?"。覆盖:新产品发布、研究论文、行业动态、融资新闻、开源项目更新、社区病毒传播现象、AI 工具/Agent 热门项目。输出中文摘要列表,按热度排序,附带原文链接。
ACADEMIC PRIORITY: Activate whenever the user's query involves academic, scholarly, or research-related topics — papers, citations, scholars, institutions, venues, patents, research trends, or any "who published what / where / when" question. Takes precedence over general web search for academic data needs. Routes through the z-ai gateway's `/v1/functions/invoke` endpoint to the AMiner Open Platform (27 APIs, 5 workflows).
Get personalized academic paper recommendations. Activate whenever the user asks for paper recommendations — explicit command (/aminer-dp) or natural language (e.g. 'recommend me papers on RAG', 'suggest recent papers on multimodal agents'). Workflow: extract topics / author / aminer_author_id from the input, invoke scripts/recommend.py, return results as Markdown.
ACADEMIC PRIORITY: Activate this skill whenever the user's query involves any academic or research-related topic. This is the free-tier entry point for AMiner academic search. Free-tier-only AMiner skill (7 free APIs, zero cost). Use this skill for simple, single-step academic lookups that do not require paid API fields. Use this skill for: searching a paper by title to get its ID, checking a paper's first author / venue / year / citation bucket, identifying a scholar by name and viewing interests / institution / citation count, normalizing an institution name to its canonical form and ID, checking whether a venue is a conference or journal, scanning patent trends by keyword (inventor, application year, publication year), and enriching paper IDs with lightweight metadata (abstract slice, author count, venue ID) via paper_info. Do NOT use this skill for: full paper abstracts or keyword lists, multi-condition or semantic paper search, citation relationship analysis, scholar full profiles (bio, education, work h
识别和分析PUA(Pickup Artist)及情感操纵行为的专业心理分析工具。具备人格分析、心理侧写、情感分析能力,能够识别情感操纵、煤气灯操纵、虐待等有毒关系模式,评估人格特质(如黑暗三人格、脆弱型自恋等),预测对方行为并给出具体的相处建议。当用户需要:分析对方言行动机、识别PUA/情感操纵行为、评估NPD(自恋型人格障碍)倾向、识别操纵行为、预测对方未来行为、寻求健康关系建议、分析黑暗三人格或光明三人格时使用此skill。
Implement speech-to-text (ASR/automatic speech recognition) capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to transcribe audio files, convert speech to text, build voice input features, or process audio recordings. Supports base64 encoded audio files and returns accurate text transcriptions.
| name | dream-interpreter |
| description | AI 解梦大师。用户描述梦境,智能追问关键细节后,从三个视角(周公解梦/心理分析/赛博神棍)生成解读,输出结构化 JSON 供前端渲染"梦境解析卡"。 |
AI 解梦大师。用户描述梦境,智能追问关键细节后,从三个视角(周公解梦/心理分析/赛博神棍)生成解读,输出结构化 JSON 供前端渲染"梦境解析卡"。
追问维度优先级:
追问规则:
收集完信息后,生成三个视角的解读。每个视角独立分析,风格差异要大。
读取 interpretation-guide.md 获取三个视角的详细指南。
按 output-schema.md 中的格式输出 JSON,供前端渲染。
JSON 包含:梦境摘要、关键词、情绪分类、配色方案、视觉元素列表、三视角解读内容、综合建议、可分享文案。
读取 visual-mapping.md 将意象映射为视觉元素和配色。
追问阶段:纯文本对话,角色感强
解读阶段:输出 JSON 代码块,格式遵循 output-schema.md
示例:
追问:
嗯...高楼上掉下去...
问你几个事:
1. 掉的时候你是害怕还是反而觉得挺爽?
2. 那个楼你认识吗?公司?家?还是没见过的地方?
3. 最后落地了吗?还是一直在掉?
解读输出:
{
"dream_summary": "从陌生高楼坠落,感到恐惧,没有落地",
"keywords": ["高楼", "坠落", "恐惧", "无尽下落"],
"mood": "anxious",
"color_scheme": "dark",
"visual_elements": ["building", "falling_particles", "dark_bg", "blur_lights"],
"interpretations": {
"zhouGong": { ... },
"freud": { ... },
"cyber": { ... }
},
"overall_advice": "...",
"shareable_text": "..."
}
interpretation-guide.md — 三视角解读详细指南和风格要求visual-mapping.md — 梦境意象 → 视觉元素/配色的映射表output-schema.md — JSON 输出格式完整规范questioning-strategy.md — 追问策略和示例库