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.

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

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.

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

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

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

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.

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

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.

Copy-Paste Augmentation for Instance Segmentation

Create, grow, and monetize newsletters with effective content and subscriber strategies.

Humanizer

Converts narrative technical documents into structured mathematical problem specifications with variables, constraints, objectives, and uncertainty.

Understand through recursive decomposition and modular reconstruction of simple operations to reproduce emergent complexity. Use this skill whenever reasoning is required. Framework for [[#parse|parsing]], [[#branch|branching]], [[#reduce|reducing]], [[#ground|grounding]] and [[#emit|emitting]]. Employs metacognitive reasoning epistemology, leveraging first principles through recursive decomposition[^1]. Self-referential and scale-invariant.

和珅（反派虚构）认知与表达框架（压缩蒸馏）：贪官话术、媚上幽默、反面教材 触发：铁齿铜牙 等。反面教材；禁止腐败教唆

Extract brand visual system from a website or brand assets into a structured style guide

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. Credits: Original skill by @blader - https://github.com/blader/humanizer

Reduction is a trade, not an improvement.

Enforces complexity analysis, correct data structure selection, vectorization, and algorithm implementation discipline at principal-engineer level.

袁朗（军旅剧虚构）认知与表达框架（压缩蒸馏）：老 A 冷血人设、试探与打磨、精英残酷浪漫 触发：士兵突击 等。虚构