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danielrosehill/Claude-Text-Corpus-Analysis-Plugin

SkillsMP 已收集 danielrosehill/Claude-Text-Corpus-Analysis-Plugin 中的 14 个 Skill。打开任一 Skill 可查看来源和详情。

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已展示 14 / 14 个已收集 Skill。

职业分类
数据科学家
描述

Assign each document in a corpus to one of N user-defined categories. Use when the user has a fixed taxonomy (e.g. 10-20 labels) and wants every note/document routed into exactly one (or top-k) of them. Supports zero-shot classifiers, local LLMs, and cloud…

原文语言:英语

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职业分类
数据科学家
描述

Decide whether a corpus analysis task should use classical NLP, a local LLM, or a cloud LLM (OpenRouter) given corpus size, task complexity, and cost tolerance. Use first, before any other skill in this plugin, especially when the corpus is large (thousands+…

原文语言:英语

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职业分类
数据科学家
描述

Correlate metadata (timestamps, tags, source, author) with content features (topics, entities, length, sentiment) to surface non-obvious patterns. Use when the user asks "does X correlate with Y in my corpus" or wants to discover relationships between…

原文语言:英语

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职业分类
数据库架构师
描述

Build a multi-level taxonomy (categories → tags → sub-categories) from a text corpus. Use when the user wants more than a flat category list — e.g. "give me a hierarchical taxonomy for my tech notes" or "categories, tags, and sub-tags for this corpus of…

原文语言:英语

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职业分类
数据科学家
描述

Extract named entities (people, places, organizations, dates, products) from a text corpus. Use when the user wants to know "who and where is mentioned" or needs a list of entities for downstream indexing, linking, or trend analysis.

原文语言:英语

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职业分类
数据科学家
描述

Compute summary statistics over a text corpus — average word length, words/doc, sentences/doc, lexical diversity, readability scores, token length distributions. Use when the user wants a quantitative description of the corpus shape rather than its content.

原文语言:英语

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职业分类
软件开发工程师
描述

Recommend well-maintained external libraries and tools for text corpus analysis beyond what this plugin ships — classical NLP, topic modeling, corpus indexing, aspect-based sentiment, multilingual analysis. Use when a task calls for something this plugin…

原文语言:英语

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职业分类
网络与计算机系统管理员
描述

Audit what local LLM runtimes are installed (Ollama, llama.cpp, vLLM, LM Studio) and suggest/install a model suitable for corpus analysis tasks — classification, labeling, summarization. Use when a skill in this plugin wants a local-LLM lane but nothing is…

原文语言:英语

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职业分类
网络与计算机系统管理员
描述

Configure OpenRouter as the cloud-LLM backend for skills in this plugin. Use when a skill needs cloud LLM access and the user wants pay-as-you-go routing across Claude, GPT, Gemini, DeepSeek, Llama, Qwen without managing multiple provider keys.

原文语言:英语

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职业分类
档案文员
描述

Derive N categories from the dominant themes of a corpus — the user says "give me 10 categories for these 1000 notes" or "propose 20 labels that would cover most of this data". Produces a proposed category list with definitions, coverage estimates, and…

原文语言:英语

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职业分类
数据科学家
描述

Identify tokens or phrases that refer to the same concept but appear in different forms — transcription variants from voice notes, spelling variants, acronyms vs expansions, aliases. Use on any voice-note or STT-derived corpus before frequency/NER/topic work,…

原文语言:英语

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职业分类
数据科学家
描述

Identify topic clusters in a text corpus and track how those topics evolve over time. Use when the user has a body of notes, voice notes, articles, or documents and wants to know "what is this corpus mostly about" or "how have my interests shifted". Supports…

原文语言:英语

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职业分类
数据科学家
描述

Identify temporal trends across a text corpus — rising/falling topics, entities, or keywords over time. Use after topic-analysis or ner-extraction when the user wants "what am I talking about more / less than before" or "when did X first show up".

原文语言:英语

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职业分类
数据科学家
描述

Count word/token occurrences across a corpus with stopword filtering, stemming/lemmatization options, and n-gram support. Use when the user wants a simple frequency export — "how often does X come up", "top 100 words in my notes", "bigram frequencies".

原文语言:英语

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已展示 14 / 14 个已收集 Skill。