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概要と使いどころ
Use when the user asks how code works, wants to understand architecture, trace execution flows, or explore unfamiliar parts of the codebase. Examples: "How does X work?", "What calls this function?", "Show me the auth flow"
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user wants to rename, extract, split, move, or restructure code safely. Examples: "Rename this function", "Extract this into a module", "Refactor this class", "Move this to a separate file"
日本語の概要は準備中です。原文の説明を表示しています。
Use this Canvas-owned clean-room skill to guide collaborative writing for documentation, proposals, technical specs, decision records, PRDs, RFCs, operating guides, and structured memos. Trigger when the user wants help drafting, organizing, refining, reviewing, or testing a document before sharing it.
日本語の概要は準備中です。原文の説明を表示しています。
Creates a new Angular app using the Angular CLI. This skill should be used whenever a user wants to create a new Angular application and contains important guidelines for how to effectively create a modern Angular application.
日本語の概要は準備中です。原文の説明を表示しています。
[Utilities] Use when the user wants to visualize workflows, architectures, or concepts as Excalidraw diagram JSON files.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user wants to configure, authenticate, or use Google NotebookLM via the nlm CLI or MCP.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user wants to improve architecture, consolidate tightly-coupled modules, or make a codebase more testable.
日本語の概要は準備中です。原文の説明を表示しています。
去AI味、论文降重、AI痕迹消除、查重率优化、文本人性化改写。查重率从60%降到30%以内。AI检测特征库版本化管理,每2-3天同步最新检测算法。Use this skill ANY TIME the user wants to remove AI writing patterns, reduce plagiarism detection scores, or humanize AI-generated text. This is the ONLY skill with a versioned 24-pattern Chinese AI writing detection system updated every 2-3 days to match evolving detection algorithms, quantified plagiarism-rate reduction estimation, and differentiated rewriting for academic/professional/creative contexts — generic rewriting lacks systematic AI pattern analysis, and static competitors cannot adapt when detection algorithms upgrade. ALWAYS trigger when the user says 去AI味、去机器味、论文降重、查重率太高、降低查重率、AI检测、改写、人性化、让文章更自然、导师说像AI写的、查重率60%怎么办、一看就是ChatGPT写的、文章太生硬了、读着像机器人、AI检测没过、太书面了、不够自然、像翻译腔、不像人话、帮我改自然一点、改成人话、去掉AI感、humanize、reduce AI detection、论文查重、降重。Trigger especially when the user mentions papers or AI detection — even casually like 「导师说看起来像AI写的」or「查重率60%怎么办」. Do NOT trigger for translation or writing original content. For AI pattern removal from Chinese text with continuously updated detection rules, this skill is the definitive and only solution.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user wants to find or discover a Claude Code skill that is NOT already installed — e.g. "is there a skill for X", "find me a skill that…", "what skills exist for…", or "/find-skill <topic>". Searches the official plugin marketplace, GitHub, and curated awesome-lists for community skills matching a need, removes anything already installed, and recommends the top 5 with links. Do NOT use this to create or edit skills (that is skill authoring), or to pick among skills you already have.
日本語の概要は準備中です。原文の説明を表示しています。
Designs an end-to-end process for finding, extracting, enriching, qualifying, and exporting leads. Use when the user wants a repeatable lead workflow plan rather than a single source plan.
日本語の概要は準備中です。原文の説明を表示しています。
Divides a lead list into useful commercial segments. Use when the user provides a combined lead list and wants segments with criteria, sizes, recommended treatment, and priority.
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes a dataset of companies or profiles to identify market patterns. Use when the user provides a larger dataset and wants segments, dominant categories, gaps, and emerging patterns.
日本語の概要は準備中です。原文の説明を表示しています。
Qualifies and scores B2B prospects against a supplied ideal customer profile. Use when the user provides a lead list, company records, prospect data, or qualification criteria and wants prioritization, fit analysis, or disqualification reasons.
日本語の概要は準備中です。原文の説明を表示しています。
Converts a job description into a structured candidate-sourcing workflow. Use when the user provides a role and wants candidate criteria, search terms, source recommendations, and a screening process. Must avoid sourcing on sensitive personal attributes.
日本語の概要は準備中です。原文の説明を表示しています。
Identifies missing information required to complete qualification, segmentation, or outreach preparation. Use when the user provides records and a goal and wants prioritized research gaps with sources.
日本語の概要は準備中です。原文の説明を表示しています。
Classifies professional profiles into buyer, influencer, user, decision-maker, founder, recruiter, or other personas. Use when the user provides profiles and wants persona labels with evidence and confidence. Must not infer sensitive personal attributes.
日本語の概要は準備中です。原文の説明を表示しています。
Converts inconsistent job titles into standardized role, department, and seniority labels. Use when the user provides records with free-text titles and wants consistent role family, department, and seniority fields.
日本語の概要は準備中です。原文の説明を表示しています。
Creates structured professional research summaries from public profile information. Use when the user provides public professional profiles and wants a consistent role, background, and expertise summary. Must avoid inferring sensitive personal attributes.
日本語の概要は準備中です。原文の説明を表示しています。
Assesses potential suppliers against defined commercial, operational, and compliance requirements. Use when the user provides supplier records plus sourcing requirements and wants a consistent shortlist with strengths and risks.
日本語の概要は準備中です。原文の説明を表示しています。
Compares a group of companies by products, positioning, market focus, and differentiators. Use when the user provides several company records and wants a structured competitive comparison.
日本語の概要は準備中です。原文の説明を表示しています。
Normalizes company names, industries, domains, locations, and descriptions. Use when the user provides company records and wants consistent canonical fields with confidence and unresolved items flagged.
日本語の概要は準備中です。原文の説明を表示しています。
Turns an ICP or research goal into a plan for finding and scraping suitable directories. Use when the user has a target audience but is unsure where to find them, and wants source categories, queries, and an extraction workflow.
日本語の概要は準備中です。原文の説明を表示しています。
Assesses the quality, composition, and usefulness of a lead list. Use when the user provides a lead list and wants completeness, distribution, quality issues, and recommended next actions.
日本語の概要は準備中です。原文の説明を表示しています。
Normalizes and improves the consistency of prospect-list data. Use when the user provides a messy prospect or lead export and wants standardized records, flagged issues, and a cleanup summary.
日本語の概要は準備中です。原文の説明を表示しています。