Results for “substantiierung”

Create a structured specification file for a solution component, optimized for Generative AI consumption.

Create Zustand stores with TypeScript, subscribeWithSelector middleware, and proper state/action separation for React state management.

Creates .NET projects from templates with validated parameters, Central Package Management adaptation, and multi-project composition.

Train or fine-tune sentence-transformers models for retrieval, similarity, clustering, classification, and reranking, with support for bi-encoders, cross-encoders, and sparse encoders.

Use when content is verbose, repetitive, or padded and needs tightening while preserving meaning

Summarize text using extractive, abstractive, hierarchical, and multi-document techniques, producing concise outputs at configurable detail levels. Use when the user requests summarization or provides relevant inputs for this workflow.

Lossless LLM-optimized compression of source documents. Use when the user requests to 'distill documents' or 'create a distillate'.

润色中文学术论文，识别并替换模板化、机械化的AI表达，使文本更自然、更符合人类学者的写作习惯。

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md. Identifying inconsistencies, duplications, ambiguities, and underspecified items.

Brainstorm product positioning ideas differentiated from competitors, generating positioning statements with strategic rationale.

Transforms plain text or markdown into well-structured, reader-friendly markdown with frontmatter, titles, summaries, headings, bold, lists, and code blocks.

Multi-dimensional lead qualification scoring. Evaluates leads against BANT criteria, firmographic fit, behavioral signals, and intent indicators. Outputs qualified/disqualified verdict with detailed reasoning.

Creates a structured, queryable snapshot of a domain's current state, capturing entities, relationships, and properties with confidence scores and evidence anchors.

Structural editor that proposes cuts, reorganization, and simplification while preserving comprehension. Use when user requests structural review or editorial review of structure

Knowledge-base steward in the spirit of Niklas Luhmann's Zettelkasten. Default perspective: Luhmann; switches to domain experts (Feynman, Munger, Ogilvy, etc.) by task. Enforces atomic notes, connectivity, and validation loops. Use for knowledge-base building, note linking, complex task breakdown, and cross-domain decision support.

Strip designs to their essence by removing unnecessary complexity. Great design is simple, powerful, and clean.

Analyzes keyword usage in provided content, calculates density, suggests semantic variations and LSI keywords based on the topic. Prevents over-optimization. Use PROACTIVELY for content optimization.

Identify underspecified areas in the current feature spec by asking targeted clarification questions and encoding answers back into the spec.

Transforms video or audio transcripts into structured markdown documentation, organizing content by topic with configurable styles and source attribution.

佟年（都市剧虚构）认知与表达框架（压缩蒸馏）：甜妹直球、学霸恋爱、软萌坚持 触发：亲爱的热爱的 等。虚构

Strip designs to their essence by removing unnecessary complexity. Great design is simple, powerful, and clean.

Conduct structured, multi-session brand identity interviews to produce a master brandbook covering purpose, positioning, audience, personality, voice, narrative, and founder-brand tension.

Build and run the owner's self-branding system in a structured way across LinkedIn, Substack, dev.to, X, profile rewrites, recurring series, and comment strategy. Use when the owner asks for positioning, a branding plan, profile updates, content drafts, a publishing sequence, comment ideas, or help maintaining a consistent public voice. Optimize for operator credibility: specific experience, defensible numbers, concrete artifacts, and category ownership.

Master Test Architect and Quality Advisor. Use when the user asks to talk to Murat or requests the Test Architect.

Detect and humanize AI-generated Chinese text. 20+ rule detection categories plus statistical features (sentence-length CV, short-sentence fraction, comma density, perplexity, GLTR, DivEye) plus scene-aware LR fusion (rule × 0.2 + LR × 0.8) trained on three scenes: general / academic / longform 长文本 (≥1500 字)。Unified CLI: ./humanize {detect,rewrite,academic,style,compare}. 8 style transforms (casual/zhihu/xiaohongshu/wechat/academic/literary/weibo/novel)。 Multi-paragraph rewriting (paragraph length CV、跨段 trigram 重复) plus best-of-N humanize (默认 N=10 取最低 LR)。165 replacement patterns + CiLin 同义词词林 38873 with collision blacklist。 Academic paper AIGC reduction for CNKI/VIP/Wanfang (知网/维普/万方 AIGC 检测降重)。 Pure Python, no dependencies, offline。v5.0.0 — HC3 fused 准确率 95%、学术 hero 100→35 (-65)、 工作汇报 96→13 (-83)、长篇博客 96→41 (-55)。 Use when user says: "去AI味", "降AIGC", "人性化文本", "humanize chinese", "AI检测", "AIGC降重", "去除AI痕迹", "文本改写", "论文降重", "知网检测", "维普检测", "AI写作检测", "让文字更自然", "detect AI text", "humanize text", "reduce AIGC sc

去除文本中的 AI 生成痕迹。适用于编辑或审阅文本，使其听起来更自然、更像人类书写。 基于维基百科的"AI 写作特征"综合指南。检测并修复以下模式：夸大的象征意义、 宣传性语言、以 -ing 结尾的肤浅分析、模糊的归因、破折号过度使用、三段式法则、 AI 词汇、否定式排比、过多的连接性短语。

Structured brainstorming for projects and features. Explores multiple options before implementation.

Push the LLM to reconsider, refine, and improve its recent output. Use when user asks for deeper critique or mentions a known deeper critique method, e.g. socratic, first principles, pre-mortem, red team.

Publication Specialist - Writing, Review, Pre-registration & Quality Assurance Light VS applied: Avoids template-based writing + audience-specific message design Absorbed G3 (Peer Review Strategist), G4 (Pre-registration Composer), F1-F3 (Quality functions) capabilities Use when: writing abstracts, creating summaries, peer review response, pre-registration, reporting checklists, reproducibility Triggers: abstract, plain language, press release, summary, communication, peer review, revision, pre-registration, OSF, PRISMA, CONSORT, reproducibility

Formalizes narrative technical documents into structured mathematical problem specifications with variables, constraints, objectives, and uncertainty, citing evidence and flagging missing information.

Analyzes multiple provided pages to identify keyword overlap and potential cannibalization issues. Suggests differentiation strategies. Use PROACTIVELY when reviewing similar content.

Synthesize personas and jobs-to-be-done from evidence with confidence levels. Use when: (1) audience segmentation, (2) messaging alignment, (3) feature prioritization inputs. NOT for: stereotype-based profiling.

Type design analysis — encapsulation, invariant expression, usefulness, and enforcement.

当需要在写作中与读者建立情感连接、放大问题严重性，并引出后续解决方案时

Deconstruct vague business concepts into atomic-level clarity using Wittgenstein's language philosophy and Austrian economics.