3,942 件 ・ 関連度順
概要と使いどころ
Code learning and audit framework. Analyze any codebase — new, legacy, or AI-generated — and produce educational explanations or architectural audits. Use when the user wants to understand WHAT and WHY behind any code, not just accept 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。
Automatically invoke this skill whenever the user asks to refresh a semantic model or a dataset. Can also be used to manage, optimize, troubleshoot, or configure a refresh or a refresh schedule.
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。
Expert guidance for the cross-platform Tabular Editor CLI (the `te` binary, currently in preview) that manages Power BI / Analysis Services semantic models from the terminal on macOS, Linux, and Windows. Use when the user mentions the `te` CLI or "Tabular Editor CLI" (not the "2"), or runs a `te <command>` to scaffold, inspect, edit, validate, run BPA on, query, deploy, refresh, test, or migrate a semantic model. Not for the legacy Windows-only `TabularEditor.exe` (TE2).
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。
This skill should be used whenever the user mentions a "semantic model", "data model", or "dataset", or asks to "build", "model", "design", "optimize", "review", or "audit" one, or to "add a measure", "add a relationship", "create a role" / "set up RLS", "add a calculation group", "set up incremental refresh", "fix a star schema", "reduce model size", "prepare a model for Copilot / AI", or "check model quality". Covers the full lifecycle (design, build, refresh, review) and drives every operation through the `te` CLI first, then TOM (connect-pbid) or a model MCP, then TMDL authoring (the tmdl skill). Not for report visuals (use pbir-cli) or isolated DAX query tuning (use the dax skill).
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。
DAX performance optimization for semantic models. Automatically invoke when the user asks to "optimize DAX", "fix slow DAX", "DAX performance", "tune a measure", "debug a measure", "DAX anti-patterns", or mentions slow queries, server timings, or DAX authoring.
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。
Reduce defensive writing in drafts and revisions by removing unnecessary caveats, disclaimers, hedges, apology-like framing, negative self-limiting statements, and over-explanations while preserving necessary scope, accuracy, safety, legal, ethical, and methodological limits. Use when drafting or revising academic writing, papers, essays, abstracts, introductions, contribution statements, discussions, conclusions, technical explanations, grant writing, product writing, policy writing, professional reports, or any text the user wants to be clearer, stronger, more direct, more concise, more confident, less verbose, less caveated, less apologetic, or less defensive.
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。
Analytics engineering across data modeling, dbt, transformation, and semantic layers. Use when building dbt models, designing star schemas, writing staging or mart SQL, configuring data tests, or optimizing warehouse queries.
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。
This skill should be used when the user asks to "build web automation scripts", "check browser automation for detection", "generate web scraping code", "create form filling automation", or "build anti-detection browser scripts".
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。
Bypasses anti-bot protections using Oxylabs Web Unblocker, an AI-powered proxy that handles fingerprinting, JavaScript rendering, and retries automatically. Use when the user needs to scrape protected websites, bypass CAPTCHAs, access blocked content, or when regular proxies fail due to anti-bot measures.
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。
Rigorous multi-pass editor for law review articles, student notes, seminar papers and other legal scholarship. Runs six specialized passes — structure, substantive critique, Bluebook citations, grammar and clarity, fact-checking against sources, and a synthesizing memo — and delivers an editorial memo with issues prioritized as critical, substantial or minor and keyed to specific footnotes and paragraphs. Handles articles of any length, including 50,000-word pieces, by chunking on section boundaries. Reads .docx directly. Use when editing, critiquing, workshopping or pre-submission-reviewing academic legal writing. Triggers on "edit my article," "review this draft," "critique my note," "check my Bluebook citations," "is my argument sound," "read my law review piece," "workshop this paper," "pre-submission review." Chunking needs Python 3; fact-checking needs web search; both degrade gracefully without.
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。
Design structured perspective-taking activities with anti-projection guardrails. Develops genuine understanding of complexity across history, social sciences, and literature — not performed empathy.
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。
Agentic eyes for Godot work: cross-platform screenshot CLI (asset/region/window/screen) to budgeted WebP, TEMP editor viewport bridge under .gdskills/, and Taste Receptor Atlas v2 (~237 micro-receptors × 0–2: hierarchy, contrast, typography×41, affordance, space, color, icon, composition, light/FX, motion-tells, anti-slop, originality, identity). Use when agents must see UI, assets, or the editor — not for in-game screenshot Autoloads. Keywords: agent vision, screenshot, WebP, visual QA, taste receptors, typography, UI review, asset sheet, editor viewport, anti-slop.
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。
Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
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。
SERP-based semantic topic clustering for content architecture planning. Groups keywords by actual Google SERP overlap (not text similarity), designs hub-and-spoke content clusters with internal link matrices, and generates interactive visualizations. Optionally executes content creation if codex-blog is installed. Use when user says "topic cluster", "content cluster", "semantic clustering", "pillar page", "hub and spoke", "content architecture", "keyword grouping", or "cluster 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。
The analysis and visualization of alternative splicing (AS) events from RNA sequencing data remains challenging. SpliceWiz is a user-friendly and performance-optimized R package for AS analysis, by processing alignment BAM files to quantify read counts across splice junctions, IRFinder-based intron retention quantitation, and supports novel splicing event identification. We introduce a novel visualization for AS using normalized coverage, thereby allowing visualization of differential AS across
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。
The semantic comparisons of Gene Ontology (GO) annotations provide quantitative ways to compute similarities between genes and gene groups, and have became important basis for many bioinformatics analysis approaches. GOSemSim is an R packag
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。
The QFeatures infrastructure enables the management and processing of quantitative features for high-throughput mass spectrometry assays. It provides a familiar Bioconductor user experience to manages quantitative data across different assa
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。
BEER implements a Bayesian model for analyzing phage-immunoprecipitation sequencing (PhIP-seq) data. Given a PhIPData object, BEER returns posterior probabilities of enriched antibody responses, point estimates for the relative fold-change in comparison to negative control samples, and more. Additionally, BEER provides a convenient implementation for using edgeR to identify enriched antibody responses.
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。
Find the papers that answer a research query in Firecrawl's research paper index — a corpus of paper abstracts whose largest share is biomedical and life-science literature (PubMed, bioRxiv, medRxiv), alongside arXiv preprints in CS, physics, and math — using semantic search, semantic and structural expansion, and in-body verification. Use this skill for literature-finding and paper-retrieval tasks of any kind, including clinical, biomedical, drug, gene, disease, and other life-science questions, whether the answer is a single paper or a full multi-paper set. The index is reached only through the `firecrawl_research_*` MCP tools or the `firecrawl research` CLI subcommands. Calling `firecrawl_search` with its `categories` option set to `["research"]` is a different feature — it filters ordinary web search to research-affiliated websites (the list includes PubMed, bioRxiv, medRxiv, arXiv, and publisher sites) and returns page results from them, without querying the paper records in this index.
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。
Provides reverse engineering techniques. Use when the main job is to understand how a compiled, obfuscated, packed, or virtualized target works before exploiting or solving it, including binaries, APKs, WASM, firmware, custom VMs, bytecode, malware-like loaders, and anti-debug or anti-analysis logic. Do not use it when the vulnerability is already understood and the remaining task is exploitation; use pwn instead. Do not use it for pure web workflows, log or disk forensics, or standalone crypto problems unless reversing the implementation is the real blocker.
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。
Remove AI writing patterns from academic prose. Detects and fixes inflated symbolism, promotional language, superficial analyses, vague attributions, AI vocabulary, and formulaic structures. Supports English and Chinese. Triggers on "remove AI patterns", "humanize text", "anti-AI polish", "去除AI写作痕迹", "人性化处理".
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。
Comprehensive R package for command-line interface styling, semantic messaging, and user communication. Use this skill when working with R code that needs to: (1) Format console output with inline markup and colors, (2) Display errors, warnings, or messages with cli_abort/cli_warn/cli_inform, (3) Show progress indicators for long-running operations, (4) Create semantic CLI elements (headers, lists, alerts, code blocks), (5) Apply themes and customize output styling, (6) Handle pluralization in user-facing text, (7) Work with ANSI strings, hyperlinks, or custom containers. Also use when migrating from base R message/warning/stop, debugging cli code, or improving existing cli usage.
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。
DO NOT INVOKE when the primary request explicitly asks to convert, migrate, modernize, or rewrite a legacy/old-style project to SDK style; use msbuild-modernization. Migration prompts often mention ToolsVersion, explicit Compile/Reference entries, packages.config, or Microsoft.CSharp.targets, but merely reviewing or auditing a file that contains those patterns remains in scope here. USE FOR broad review, audit, lint, or maintainability/correctness checks of project/build files, including custom targets; prioritized cross-cutting findings; discrete anti-patterns; F# ordering/FS0039; cross-platform paths; and focused Import safety verdicts. Review/audit is analysis-only unless fixes are requested. For concrete property/item defects use property-patterns/item-management; use target-authoring for implementation and extension-points for NuGet auto-import/layout discovery. Exclude non-MSBuild systems.
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。
Own concrete MSBuild ItemGroup and item-expression questions. USE FOR: Include, Remove, Update, item identity and metadata, transforms, filtering, batching, duplicate or overlapping items, and reviews that verify whether those operations are correct. Generated items stay in scope when the central defect is item identity, metadata, batching, duplicate declarations, or glob/Remove/Update semantics. For a generated artifact missing from compilation or output, wrong target timing/path, or FileWrites clean tracking without a broader item-semantics defect, use including-generated-files. The item operation may be broken, suspected, or already correct. Exclude property-only issues, general incrementality with no item question, broad reviews with no concrete item concern, and non-MSBuild systems.
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。