3,957 件 ・ 関連度順
概要と使いどころ
Enforce session-cost telemetry and execution-metadata reporting. Use when explicitly invoking get_session_cost, reporting token/cost usage, applying telemetry or cost guidance during a workflow handoff, or writing artifacts/session-cost.md at a workflow terminal state.
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。
Infer the requesting operator's technical fluency from message content (never ask directly) and adapt register — business, hybrid, or technical — across SDLC workflow output. Use when starting sdlc, brainstorm-feature, plan-feature, verify-work, publish-notes, or session-report, or whenever a request's phrasing signals a non-technical or cross-stack operator.
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 and reviews detections from telemetry prerequisites, correlation logic, Sigma metadata, severity, status, and benign cases. Use for detection rules, Sigma review, analytic coverage, or tuning; not generic logging advice or live deployment.
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。
Enforce SOLID principles, guard-clause style, function size limits, and intention-revealing naming across all languages. Use when refactoring for readability, applying clean-code patterns, reviewing naming conventions, or reducing function complexity.
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。
Helps a teacher prepare to teach an existing K-12 lesson (math / ELA / science / social studies) — a prep partner that thinks through the lesson's key student task with the teacher and leaves a short teacher-only prep note. Triggers on asks to internalize, prepare for, get ready to teach, or understand a lesson, including implicit ones ("help me get ready for tomorrow's lesson"), and right after another skill built a lesson, which it can follow. Not for building or adapting a lesson, grading, rubrics, assessment feedback, or generating quizzes or student-facing material, and not for single-fact lookups a sentence would answer ("what standard is this?", "how long is this lesson?").
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 design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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。
提取PDF文件的元数据（标题、作者、主题、页数等），输出为JSON格式。当用户需要查看PDF文档信息时使用此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。
提取 PDF 文件元数据并输出 JSON 结果。 当用户提到把这次流程沉淀成 skill、保存为 skill等需求时使用此 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。
Performs security-focused differential review of code changes (PRs, commits, diffs). Adapts analysis depth to codebase size, uses git history for context, calculates blast radius, checks test coverage, and generates comprehensive markdown reports. Automatically detects and prevents security regressions.
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 skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.
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。
Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research 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。
멀티 에이전트 디자인 워크플로우 supervisor. writer, locale adaptation, humanize, UI slop audit, designer review, final QA, image materialization을 routing한다. 2-round revision cap을 유지하며 다국어 문서·UI 개선·출간 준비처럼 여러 역할이 필요한 요청에 사용한다.
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。
멀티 에이전트 디자인 워크플로우 supervisor. writer, locale adaptation, humanize, UI slop audit, designer review, final QA, image materialization을 routing한다. 2-round revision cap을 유지하며 다국어 문서·UI 개선·출간 준비처럼 여러 역할이 필요한 요청에 사용한다.
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 similar vulnerabilities across a codebase after discovering one instance. Uses pattern matching, AST search, Semgrep/CodeQL queries, and manual tracing to propagate findings. Adapted from Trail of Bits. Use after finding a bug to check if the same pattern exists elsewhere.
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。
Agent basina token kullanimi takibi, maliyet optimizasyonu, butce limitleri ve ROI analizi. Session ve proje bazinda harcama raporlari. Hangi agent ne kadar token tuketiyor, hangisi verimli, hangisi israf.
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。
Identify dangerous API footguns, surprising default behaviors, and sharp edges in codebases and dependencies. Adapted from Trail of Bits. Use during code review to catch APIs that are easy to misuse, configurations that surprise, and abstractions that leak.
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。
Property-based testing (PBT) patterns with fast-check (JS/TS), Hypothesis (Python), and gopter (Go). Generate random inputs, define invariants, shrink failures to minimal cases. Adapted from Trail of Bits. Use when testing pure functions, parsers, serializers, state machines, or any code where example-based tests miss edge cases.
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-to-implement pipeline chaining 5 MCP tools with graceful degradation
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。
Hızır'ın kullanım kılavuzu. Tüm komutlar, agent'lar, workflow'lar, sistemler burada. /hizir yaz, her şeyi gör.
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。
Detect fail-open configurations, hardcoded secrets, weak authentication defaults, permissive CORS, disabled security features, and other insecure-by-default patterns. Adapted from Trail of Bits. Use during security review or when auditing configuration and initialization code.
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。
Systematic false positive verification for security findings. Provides structured methodology to confirm or dismiss scanner results, manual audit findings, and automated alerts. Adapted from Trail of Bits. Use when triaging security scan results or verifying audit findings.
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。
React error boundary hierarchy, fallback UI patterns, offline-first fallback, retry mechanisms, and graceful degradation.
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。
Implements media and file management components including file upload (drag-drop, multi-file, resumable), image galleries (lightbox, carousel, masonry), video players (custom controls, captions, adaptive streaming), audio players (waveform, playlists), document viewers (PDF, Office), and optimization strategies (compression, responsive images, lazy loading, CDN). Use when handling files, displaying media, or building rich content experiences.
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。
Retrieve arXiv paper metadata with keyword queries or import an offline arXiv export, and save results as JSONL (`papers/papers_raw.jsonl`).
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。