2.3万 件 ・ 関連度順
概要と使いどころ
Generate social media announcements for Discord, Twitter/X, Facebook, and LinkedIn from the latest changelog entry. Use when user asks to 'create release announcement' or 'create social posts' or share changelog updates.
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。
Bring past diagnoses to a bug before fixing it, record the new root-cause hypothesis, and close it as confirmed or refuted once the fix is verified. Use when a bug could come from more than one layer, or looks like something seen before.
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。
Operate Jira Cloud via its REST v3 API — issues, projects, sprints, boards, comments, transitions, JQL search. Use when the user wants to triage, bulk-update, report on, or otherwise interact with Jira programmatically without the MCP server installed.
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。
Operate Stripe's REST API — customers, payments (PaymentIntents / Charges), refunds, subscriptions, invoices, Checkout Sessions, products/prices, payouts, disputes. Use when the user wants to query or mutate Stripe data programmatically without the MCP server or the Dashboard.
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。
Discover and execute specialized skills from a curated marketplace catalog on GitHub, fetched on-demand and run ephemerally (no permanent installation). The catalog covers a broad and growing range — document generation (PDF/Word/Excel/PowerPoint), visual design, presentations, web app testing, animated GIFs, dev tooling (MCP scaffolding, frontend components), creative outputs (algorithmic art), technical documentation lookup (library/API/framework references), and more. Consult this skill whenever the user asks for a capability that could plausibly be covered by a community skill — the catalog is the source of truth, not this description.
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。
Query PostHog product analytics via REST API — event analytics, HogQL SQL queries, feature flags, experiments, session recordings, insights, persons, cohorts. Use when the user wants to answer an analytics question, toggle/inspect a flag, or pull event data programmatically without opening the PostHog UI or installing the PostHog 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。
Prepare and launch LoRA, LoKr, or T-LoRA training through lora-scripts-next (SD-Trainer), Anima-first. Use when the user asks to train a character, style, or concept LoRA, choose parameters or repeats and epochs, start a run, or monitor training on Anima, SD1.5, SDXL, or Flux. Organize and caption the dataset, run dataset-doctor, choose a documented starting preset from image count and VRAM, show one confirmation card, then call the mikazuki API and monitor its log.
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。
Build an Anima LoRA from a single-character or style name, from Danbooru collection through curation, section-ordered WD14 captions, dataset checks, confirmed training, fixed-seed checkpoint validation, and a staged Civitai draft. Use for requests such as make a LoRA of X, collect images and train a character LoRA, train and upload to Civitai, or build a dataset from scratch and publish. Delegate training to lora-trainer and structural checks to dataset-doctor; never train without confirmation and never auto-publish.
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。
Embedded firmware setup: STM32, ESP32, AVR, RP2040, Nordic nRF, Zephyr/RTOS, vendor SDKs, CMake/CMakePresets, VS Code/clangd, cross toolchains, flash/debug, Docker/CI. Use for MCU scaffolds, existing firmware modernization, BSPs, linker/startup files, SDK package selection, and embedded CI; prefer cpp-project-setup for host-side C++.
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 reviewing, debugging, or improving TBQ3/TB language code for trading correctness, Bar strategy behavior, order direction, position state, sizing, costs, backtest realism, event timing, multi-symbol logic, or function documentation consistency.
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。
Transform an ordinary object in a supplied photo into a poetic museum-exhibit poster, preserving its identifying shape while reimagining the display setting. Use for 私人生活博物馆, 日常物件展品, or a collectible still-life poster from food, flowers, toys or personal objects.
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。
複雑なコードベースを体系的に分析し、アーキテクチャを可視化・ドキュメント化して新規開発者のオンボーディングを支援する汎用スキル。成果物は必ず `docs/` 配下に分割出力する。以下のリクエストで使用する：(1)「このコードベースを分析して」「全体像を教えて」など概要把握、(2)「アーキテクチャドキュメントを作って」「C4図を生成して」など設計ドキュメント生成、(3)「オンボーディング資料を作って」など新規開発者向け資料作成、(4)「技術的負債を洗い出して」など負債評価、(5)「機能一覧を出して」など機能インベントリ生成、(6)「この機能を操作したら何が起きるか追跡して」などユーザー操作フロー追跡、(7)「新機能の実装手順を出して」などフロント／バック横断の実装ガイド生成。特定の言語・フレームワーク・ディレクトリ構成に依存せず、どのリポジトリでも利用できる。
Senior engineer CLI expertise for AI agents — workflows, safety guardrails, gotchas, and anti-patterns across cloud, IaC, containers, databases, dev tools, and platforms
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。
Research any open-source repository end to end and answer the core question — SHOULD YOU contribute to it? — with a GO / NO-GO / GO-IF verdict backed by evidence: snapshot, momentum, contribution landscape (PR acceptance rates, outside-contributor merge rates, first-timer outcomes), issue health, governance, community sentiment, and a final go/no-go recommendation. Use when the user asks 'should I contribute to X', wants a before-I-contribute due-diligence check on a project, asks whether a project accepts outside PRs, wants contribution-health numbers like PR merge rates or stale-PR counts, or asks for a deep dive on an open-source codebase's health and dynamics before investing time in 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。
Deployless delivery-model audit. Use first when adapting any repository toward single-mainline development, automatic deployment from main, runtime release controls, production-trace-driven iteration, AI PR governance, or multi-agent delivery workflows.
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 screenshots, websites, moodboards, competitors, or visual examples are provided and the task needs design DNA extraction, comparison, remixing, or translation into an original design direction.
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 for release-level accessibility and performance review, including WCAG 2.2 AA, keyboard/focus, target size, reduced motion, semantic controls, Core Web Vitals, images/fonts/JavaScript, and animation or 3D performance budgets.
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。
Polish, restructure, or translate academic prose into Nature-leaning English using writing-strategy principles, curated Nature/Nature Communications article patterns, and phrase-level support from Academic Phrasebank. Use whenever the user asks to polish a manuscript paragraph, abstract, introduction, results, discussion, conclusion, title, methods section, or Chinese academic draft for publication-quality English. Also covers LaTeX layout/typesetting (排版) fixes — loose or sparse pages, stranded section headings, figures that don't fill the page or split across pages, "Float too large", multi-panel figure arrangement, and Supplementary Information that looks empty — via references/latex-layout.md. Also trigger on general academic/scientific writing requests even without the word "Nature", including academic writing, scientific writing, SCI/paper writing, English manuscript polishing, language editing, proofreading, and Chinese phrasings such as 学术写作、科研写作、论文润色、写paper、SCI写作、英文论文润色、语言润色、润色、改写、学术英语、英文写作.
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。
Simulate a Nature-style reviewer assessment from the referee perspective rather than an author rebuttal. Use when the user wants a pre-submission review, reviewer report, peer-review style critique, novelty/significance/technical soundness assessment, reviewer-style manuscript evaluation, 审稿人视角评估, 预审稿意见, or Nature reviewer report. Return 3 reviewer reports plus a cross-review synthesis, grounded only in the local Nature reviewer source basis. Also trigger on general pre-submission review requests during academic writing even without the word "Nature", such as getting a mock peer review for any journal, critiquing a draft as a reviewer would, assessing novelty/rigor before submission, and Chinese phrasings like 审稿人视角、模拟审稿、预审、帮我审一下论文、投稿前自审、审稿意见模拟、找论文问题.
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。
Build full-paper Chinese-English side-by-side, figure/table-aware, source-grounded Markdown readers for journal or conference papers from PDF, DOI, arXiv, publisher HTML, or pasted text. Use whenever the user asks to translate or read a paper, make 中英文对照/原文对照/全文翻译解读, extract figures or tables into the right positions, preserve figure/table placement near relevant prose, or keep exact source anchors for every block. This skill must not degrade into a summary-only output unless the user explicitly asks for a summary. Also trigger on general paper-reading and translation requests even without the word "Nature", such as reading/translating an academic paper, literature reading, understanding a paper, and Chinese phrasings like 读论文、精读论文、论文翻译、文献翻译、文献阅读、学术阅读、帮我读这篇文章、翻译这篇paper.
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。
Build a complete but efficient Nature-style Chinese PPTX presentation from a remote-sensing, Earth-observation, geospatial AI, or broader scientific paper, preprint, PDF, article text, abstract, figure legends, or reading notes. Use this skill whenever the user asks to make slides/PPT/PPTX for journal club, group meeting, paper sharing, thesis seminar, lab meeting, department report, or academic presentation from a remote-sensing research paper. It identifies the paper type and argument, selects only the figures needed for the story, writes Chinese slide content and speaker notes, creates the actual .pptx deck, and runs an explicit self-review/corrective revision loop focused on figure quality, text overflow prevention, and non-template visual design before delivery. Also trigger on general academic-presentation requests even without the word "Nature", such as turning a paper into slides, building an academic talk deck, conference/defense presentations, and Chinese phrasings like 论文做PPT、遥感论文汇报、组会PPT、文献汇报、学术汇报、做幻灯片、讲paper、读书报告PPT.
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。
Record provenance for an Agentic MIKE+ step via the mike-plus MCP server — a manifest.json tying the model copy, inputs, edits, run QA status, result files and figures together, each file with a sha256. Use at the end of every run/compare/plot task (successful or failed) so the work can be audited, re-compared or reproduced later. No license required.
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。
Produce publication-style figures from MIKE+ .res1d results via the mike-plus MCP server — a stacked rainfall-runoff hydrograph, a single time series, a network map, a baseline-vs-scenario overlay, or a longitudinal profile (bed / crown / ground / max water level along a pipe string), in the house style (Arial 12, ticks inward, SI units, no title). Use when an agent must render MIKE+ results as a PNG without opening the GUI. No license required.
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。
Turn a timestamped rainfall CSV (design storm, gauge record, climate-scenario series) into a MIKE+ rainfall .dfs0 via the mike-plus MCP server, verified by read-back, ready to drive a model's rainfall boundary or to sit on top of a hydrograph figure. Use when the user brings rain as CSV or asks to run a model with a different storm. No license required (writing the file); wiring it into the model needs one.
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。