「its」の検索結果

One page, automated tier — run the web accessibility (a11y) rule engine against a live page and locate every violation it can detect mechanically. Pass a URL, a config target name (e.g. `accesslint:accessibility-scan dev`), or nothing to use the default target from `accesslint.config.json`. Ensures a debuggable Chrome, runs the @accesslint/core engine over CDP, and returns a worklist of live-DOM WCAG 2.2 violations, each grounded to its DOM selector and source `file:line`. Locates; doesn't edit. Use it for 'is this page accessible', 'check a11y on this URL', 'find contrast and alt-text issues', or to verify a UI change. For hands-on keyboard and screen-reader checks use `accessibility-inspect`; for a whole site or product use `accessibility-audit`; to diff against uncommitted changes or a branch use `accessibility-diff`.

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。

Safety guardrails for destructive operations. Wraps workflows and agent actions in configurable safety modes: CAREFUL (warns before destructive commands), FREEZE (restricts file edits to one directory), GUARD (both modes combined). Use when working in production, running destructive scripts, or debugging in sensitive areas. Voice triggers: "be careful", "safety on", "guard mode", "freeze scope". Also used automatically by the workflow engine when a workflow preset has safety: "guard" enabled.

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 QA testing for web applications, desktop apps, and workflows. Three tiers: QUICK (critical/high severity only — 5 min), STANDARD (+ medium severity — 15 min), EXHAUSTIVE (+ cosmetic — 30+ min). Tests user flows, finds bugs, reports with severity classification, and optionally auto-fixes with atomic commits. Produces before/after health scores and ship-readiness summary. Use when user says "test this", "QA", "find bugs", "does this work?", or "is it ready to ship?". Voice triggers: "quality check", "run QA", "test the app". For report-only (no fixes), use with --report-only flag.

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 animation from scratch, making the decisions in the order that determines whether it feels right — should it animate at all, what purpose, which tool, which properties, which curve and duration, how it interrupts, how it exits. Writes the implementation. Use when asked to animate something, add motion, make a component feel alive, or build a transition. For critiquing existing motion use review-animations; for auditing a whole codebase use improve-animations.

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。

Audits env var config: file inventory, code-to-example sync, default desync, naming, startup validation. Stack-adaptive.

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。

Audits architectural patterns against best practices. Maintains patterns catalog, calculates 4 scores per pattern. Output: patterns_catalog.md.

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。

Audits layer boundaries + cross-layer consistency: I/O violations, transaction boundaries (commit ownership), session ownership (DI vs local).

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。

Audits project physical structure: file hygiene, ignore file quality, framework convention compliance, domain/layer organization, naming conventions. Stack-adaptive via auto-detection.

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 internal compliance audits against major frameworks without hiring a consultant.

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 which AI prompts and topics matter for a brand's Answer Engine Optimization (AEO) using only free tools. Crawls a website, analyzes the brand's positioning, generates prioritized prompts people ask AI assistants, and audits existing content coverage — all without paid APIs. Use when a user wants to: find what questions people ask AI about their industry, discover AEO opportunities, research prompts for content creation, audit a site's AI visibility, or build an AEO content strategy. No API keys required — uses web_fetch, web_search (free tier), and LLM reasoning only.

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。

You are the Accessibility Engineering Engine — a complete WCAG compliance, inclusive design, and digital accessibility system. You help teams build products that work for everyone, pass audits, and...

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。

Answer Engine Optimization — get AI assistants to recommend your brand. Run AEO audits, build Answer Intent Maps, track AI recommendation positions, and maintain a 7-layer AEO infrastructure for any brand or product category.

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 Reddit seeding agent for founders. Analyzes a product spec, maps relevant subreddits, finds real threads where target users need help, drafts personalized replies and DMs, and posts approved outreach via Reddit API. Use when someone wants to find and engage their first users on Reddit, seed a product launch, or do community-led growth without a budget.

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。

Inspired by the ClawIntelligentMemory project, this skill ensures Kim Assistant's environment stays clean and its memory stays dense.

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。

You are an accessibility expert specializing in WCAG compliance, inclusive design, and assistive technology compatibility. Conduct audits, identify barriers, and provide remediation guidance.

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, configure, debug, and optimize OpenClaw AI agent deployments. Master guide for gateway configuration, openclaw.json settings, model routing and fallback chains, skills development and publishing, cron job scheduling, memory systems (Qdrant, Neo4j, SQLite), Docker infrastructure, and Tailscale VPN networking. Includes config analyzer that audits your openclaw.json and suggests improvements, plus health checker that validates all OpenClaw subsystems. Built for AI agents — Python stdlib only, no dependencies. Use for OpenClaw setup, gateway debugging, skill building, cron management, model optimization, cost reduction, and infrastructure troubleshooting.

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。

Score a repository's agentic legibility from repo-visible evidence only. Use when Codex needs to audit how easy a codebase is for coding agents to discover, bootstrap, validate, and navigate, especially for harness-engineering reviews, developer-experience audits, repo cleanup, or before/after comparisons after improving docs, tooling, or architectural constraints.

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 "implement a DiD regression", "run a staggered difference-in-differences", "set up an event study", "implement IV / 2SLS", "run a regression discontinuity design", "build synthetic control", "do propensity score matching", "test parallel trends", "run Honest DiD", "wild cluster bootstrap", "Callaway-Sant'Anna", "Sun-Abraham", "Bacon decomposition", "double machine learning", "debiased machine learning", "DML / DoubleML", "cross-fitting", "causal forest", "heterogeneous treatment effects", "ATE with ML controls", "which causal design fits my data", or needs causal-inference code, diagnostics, or identification writing in Python (StatsPAI), R, or Stata. Based on Scott Cunningham's Causal Inference: The Mixtape, with runnable validated templates, ML-based causal inference patterns, and Journal of Finance applications.

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 frontend and the user wants a distinctive / animated / "wow" UI element in React + Tailwind - e.g. a laptop-opening-on-scroll, 3D tilt card, spotlight hero, animated beams/background, marquee, bento grid, interactive globe, meteor/particle background, shimmer button, or scroll/reveal motion. Fetches the showpiece component LIVE at build time from code libraries (Aceternity, Magic UI, Cult UI, ReactBits, 21st.dev) via their shadcn registry command (or WebFetch fallback), then adapts it to brand tokens. Also covers plain components (button, form, modal, table, etc.) as a fallback. Triggers on "make it pop", "something flashy", "animated [X]", "like [cool site]", "build a [showpiece] section". NOT for non-React stacks. Inspiration galleries (Dribbble/godly) are visual reference only - never 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。

塔罗牌占星：把「抽三张塔罗牌」与「西方占星本命盘」合为一次解读。 用户带着一个具体问题来 → 抽三张牌（可复现的 seed）→ 若愿意提供生日，则用脚本 确定性地排出星座与星盘 → 用黄金黎明的塔罗↔占星对应把两者接起来（牌落在黄道哪一旬， 你的哪颗行星正站在那里）→ 给出一张交叉对照表、对所问之事的审慎取向与可执行建议。 塔罗层：牌阵位置语义、牌与牌的组合叙事、元素尊贵、正逆位、直觉对话、治疗性解读。 占星层：本命盘、相位与宫位、必然尊贵、行运盘推运、比较盘/组合盘（合盘）、太阳弧推运。 当用户说：塔罗、塔罗牌、抽牌、抽三张牌、占卜、算一卦（西洋）、牌阵、正逆位、 星盘、本命盘、星座、上升星座、月亮星座、占星、行运、流年、合盘、比较盘、 太阳弧、推运、我该不该……、这段关系会怎样、我适不适合换工作 时使用。 English triggers: "tarot", "tarot reading", "draw three cards", "what do the cards say", "spread", "reversed card", "natal chart", "birth chart", "astrology", "rising sign", "transits", "synastry", "composite chart", "solar arc", "progressions", "should I take this job", "what does my chart say". 内置离线脚本：抽牌洗牌（可复现 seed）、本命盘（行星/四轴/宫位/相位/元素统计）、 必然尊贵、牌↔盘共鸣、元素数字统计、行运盘、比较盘+组合盘、太阳弧+次限推运。 边界：要**周公解梦**请用 `zhougong-dream-interpretation`；要**四柱八字**请用 `bazi`； 要**中式黄历择日/测吉凶**请用 `zhanshi-jixiong`。本技能只做西洋塔罗与西洋占星。 即使用户只是随口说「帮我抽张牌看看」「我最近水逆吗」，也应主动使用本技能。

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。

Delegate implementation to Codex, grok, or cursor-agent, then review the diff, send it back to iterate, gate on the full test suite, and ship it as a PR. Use this whenever the user wants Codex, the grok 后端, or cursor-agent to write code, mentions handing off / delegating implementation to one of those backends, asks to work through a plan or spec unit-by-unit with an implementation backend doing the coding, or wants a review-and-merge loop wrapped around delegated output — and also when resuming such a loop ("keep going", "next unit", "继续下一个"). It encodes constraints that are expensive to rediscover: the implementer runs in the real environment behind backend-specific git and publication boundaries, must not be pointed at a full test suite by default, and its self-report is a claim rather than evidence. This loop expects an approved plan or an equivalently precise spec; settle an unsolved high-level goal into a plan first, using the engineering-mode skill when it is 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。

Research current job markets and hiring requirements, analyze recent job descriptions (JDs), compare them with a user's resume, projects, skills, and constraints, and turn evidence gaps into prioritized career actions. Use when students, job seekers, or career changers ask about current role or industry outlook (including “现在行情怎么样”), whether a role or JD fits them (including “这个JD适合我吗”), cross-platform JD sampling, resume evidence gaps or truthful tailoring, what career skill to learn next, target-role course or certificate decisions, application readiness, or a capacity-bounded 30/60/90-day job-search plan. Do not use for unrelated personal or education advice, simple factual lookups, automatic job applications, or unsupported resume rewriting.

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。

Breaks work into ordered, parallel-dispatchable tasks with an execution DAG. Output format is consumable by CI matrices and parallel agent runners — each task has a stable ID, declared file writes, conflict edges, and branch suffix. Use when you have a spec, brief, or shaper output and need to decompose it into implementable units. Use when a task feels too large, when scope spans multi-repo or multi-week work, or when parallel execution across multiple agents is on the table.

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 forensically auditing a Claude Code skill/agent/command/workflow library against RULESET.md by a fixed mechanical protocol — probing every file against the mechanically-checkable rules and reporting CONFORMS / VIOLATES / UNVERIFIABLE / N-A counts with quoted evidence. It casts NO judgment and emits NO pass/fail verdict; counts are the headline. Triggers on "investigate the library", "audit against RULESET", "find every violation", "forensic library audit", "evidence-only check". Not for routing/quality/single-responsibility judgment — use skill-library-review. Not the full sharded sweep — use the audit-library command.

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。