2,400 件 ・ 関連度順
概要と使いどころ
Use when exposing app features to App Intents, Shortcuts, Siri, Spotlight, widgets, controls, or system actions — small safe AppIntents, AppShortcutsProvider, AppEnum/AppEntity, parameters, and open-vs-background behavior.
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。
Virtual QA Lead that turns requirements into review-ready, TestRail-importable test cases in one conversation. Use it whenever the user has requirements, a spec, a user story, or acceptance criteria (PDF, DOCX, XLSX, TXT, MD, or pasted text) and wants test cases, a test plan, a checklist, test coverage, a regression suite, or a TestRail/Qase/Zephyr export, even without saying "test cases" ("write tests for this spec", "what should we check here?"). Especially useful when they attach their team's existing test cases to match. When the spec describes an API (endpoints, status codes, schemas, auth, OpenAPI/Swagger), Casely also builds a runnable Postman collection, so use it for "API tests", "Postman collection", or "tests I can run in Newman/CI". Triggers on the same request in any language.
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。
把多页 HTML 报告(主页 + N 子页 + PNG 资产)合并为单一独立 HTML / PDF / XLSX 三件交付物。 Use when finalizing a disease market sizing report and need shareable deliverables — single-file HTML for email/IM(零依赖,双击浏览器开), optional PDF for print/archive, XLSX for data export. 领域无关、跨疾病通用。 下游 of disease-market-sizing-html-template;上游 of email/IM/print 分发。 Use proactively whenever the user says "做交付物" / "生成 PDF" / "导 Excel" / "合并单文件 HTML"。
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。
Evidence-grounded AI research workflow for turning supplied economics, finance, management, and social-science papers or structured records into versioned PaperReading artifacts. Use when Codex must ingest text, Markdown, or a text-based PDF; separate source-grounded claims from researcher analysis; bind findings to evidence IDs and locators; review extraction candidates; migrate v0.2 PaperRecord JSON; validate or verify a v0.3 PaperPackage; generate research extensions; export reviewable JSON or Markdown; or safely update a compatible 13-field literature workbook.
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。
Assess AWS, Azure, and GCP controls for IAM escalation and cloud service exposure.
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。
Test Docker and Kubernetes security controls for RBAC abuse, breakout, and secret exposure.
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。
GodoMaster — Godot 4.x game development intelligence: GDScript, nodes/scenes, 2D/3D rendering, physics, animation, UI, audio, input, shaders, networking, performance, export, file I/O, testing, localization, AI behavior, asset pipeline, and architecture tooling. Complete workflow for indie and professional game development based on official Godot documentation.
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。
Builds and improves task-specific decision artifacts from application requirements and labeled records. Use for data assembly, primitive and base-model selection, fitting, export/reload, inference policy, or bounded data/model/program improvement. Includes rules and no-training outcomes; does not require a rung ladder or training a general Jev.
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。
Run authorized Xiaohongshu browser workflows for login checks, creator preview fill, publish blockers, final posting, search, export, or approved engagement. Prefer native signed-in Chrome; keep Python/CDP for deterministic batch fallback.
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。
Read and analyze Xiaohongshu comments from the user's signed-in Chrome session. Use to collect, export, summarize, or classify comments for content planning, follow-up posts, audience research, reply strategy, and 引流文案。
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。
Symptom → root-cause lookup table for nuxt-crouton's recurring failure modes — exact error strings mapped to their known cause, fix, and evidence issue. Use when you hit an error you don't recognize in this repo, before debugging from first principles. Trigger phrases and symptoms: "Cannot resolve entry module .nuxt/hub/db/schema.entry.ts", "Could not load '@fyit/crouton'", "No migrations present", "No schema files found", "$setup.t is not a function", "does not provide an export named 'Map'", "no such table: translations_ui", "collection pages 500 in production", "the build was green but the app is broken", "is this a known issue?".
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。
AI-powered design review for Figma components with weighted dual-scoring system. Evaluates Style Guide Implementation (70%) and LLM Metadata Accessibility (30%). For export, hands off to atomic-design 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。
Create, revise, and validate publication-ready academic paper figures and tables. Use for LaTeX tables, related-work comparison tables, result tables, notation/dataset/taxonomy tables, precise source-data-driven experiment plots from CSV/JSON/logs, generated conceptual figures such as system overviews/pipelines/architectures/threat models, captions, artifact specs, source-data traceability, and paper-ready PDF/SVG/PNG/LaTeX exports. Do not use for prose-only paper writing, self-review, reviewer response, rebuttal drafting, or external literature-management 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 building a new MCP server in TypeScript, Python, or C# that exposes tools to LLMs.
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 exposing a WordPress site to AI agents via MCP, or when WordPress MCP setup fails.
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。
Analyze folders of Markdown/text research notes, Obsidian vaults, paper cards, invention notes, or memory exports as a practical knowledge map. Use when asked to find center topics, noisy or low-signal notes, possible contamination, overgrown topic groups, orphan notes, cleanup actions, or a useful public knowledge-hygiene 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。
Use for DESIGN.md visual identity contracts; author, scaffold, lint, diff, and export design contracts with the upstream spec and CLI.
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。
Scrub English drafts for AI tells before publishing. Use for any English LinkedIn post or newsletter draft right after composition and BEFORE export. Removes em-dash-as-pause, weak hedges, rule-of-three patterns, AI vocabulary, negative parallelisms, and inflated symbolism. Triggers on "polish", "humanize", "make this sound human", "/polisher", or after any English composer output. Leaves Arabic and Hebrew drafts untouched — humanizer-* skills handle those.
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。
HTML-first persistent planning skill. Generates a single self-contained plan.html with interactive phases, drag-and-drop tickets, sliders, mockups, and embedded JSON state. Survives /clear via session catchup, tamper-protected by SHA-256, mirrors across 17 IDEs, ships 10 templates across Thariq's 9 categories, exports back to Markdown on demand. Use when asked to "plan it", "make me an html plan", "show me the plan", "render the plan", or when starting any multi-step task that needs a navigable artifact instead of a markdown wall.
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。
MUST USE when the user needs current, online, or web-derived information — news, latest releases, vendor docs, real-world examples, recent changes, or anything not in the model's training set. LLM-neutral skill that exposes a unified web search CLI behind a single command. Runs single or multi-provider in parallel, saves raw + normalized JSON to a temp directory, prints the path so callers can pipe through rg / jq / grep. Zero-config out of the box. Works identically on macOS, Linux, WSL, Git Bash for Windows, and any environment with Python 3.8+. Triggers: 'search the web', 'look up online', 'google this', 'find current information', 'latest news', 'recent docs', 'check the internet', 'web search', 'browser search', 'research this', 'what is the latest', 'who is X', 'find examples of', 'is there documentation for', 'how do people solve', 'web-search', 'web_search'.
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。
Scans GitHub Actions workflows and CI/CD pipeline configurations for supply chain attack vectors including unpinned actions, script injection via expressions, dependency confusion, and secrets exposure. Uses PyGithub and YAML parsing for automated audit. Use when hardening CI/CD pipelines or investigating compromised build 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。
Interactive system flow tracing across CODE, API, AUTH, DATA, NETWORK layers with SQLite persistence and Mermaid export.
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 assessing AI/ML systems for prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, or agent tool abuse. Covers MITRE ATLAS technique mapping, injection signature detection, and adversarial robustness scoring.
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。
AI-powered presentation generation via the 2slides API — create slides from text, match a reference image style, summarize documents into decks, add AI voice narration, and export pages/audio. Use for any "make slides", "create a deck", or "slides from this document" request.
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。