「view」の検索結果

Use when installing, bootstrapping, configuring, starting, verifying, operating, or troubleshooting Looper, looperd, the looper CLI, ~/.looper config, or runtime paths; when setting up Looper with opencode, claude-code, codex, cursor-cli, Grok Build, Pi, or Oh My Pi (omp); when registering repos or configuring planner/reviewer/fixer/worker loops; or when diagnosing status, logs, osascript, git, gh, LOOPER_TOKEN, writable path, or daemon startup issues.

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。

Generate App Store screenshots and header/search images for iPhone, iPad and Mac from a codebase or landing page, or re-render a set. Use when preparing a submission. Don't use for ASO keywords, review audits, icons, videos, or Google Play.

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。

Generate a commit message, stage all changes, and push to remote after scanning for secrets, large files, and protected-branch risks. Skip for opening PRs, code review, or cutting releases/tags.

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。

Install local-first security hardening: pre-commit secret detection, offline dependency scans, static analysis, reports, and gated free CI. Use when hardening repos or adding security hooks. Don't use for incident response or cloud security reviews.

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 a git repo before new work: review uncommitted changes, fix .gitignore, delete merged branches, end on clean main, or inspect one branch before deciding. Don't use for dead code, commit-and-push, releases, LICENSE files, or git how-tos.

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。

Audit a stale, inherited, or messy codebase — deps, bugs, security, tests, CI, docs, UI/UX — then emit a phased, testable modernization plan. Read-only: plans upgrades, never applies them. Not for single-PR review, PRD-to-tasks, or UX-only audits.

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。

Optimize a website or app design in one run: capture the page once, audit usability, UX/AX, virality and agent readiness, merge overlaps into one prioritized report, apply fixes on opt-in. Don't use for one lens (dont-make-me-think, ux-ax-review).

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-only context for issues, pull requests, and backlogs. Use to trace related work, check PR counts, prioritize follow-ups, filter saved captures, open exact dashboard views, replay triage queries, or compare snapshots.

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。

Write, review, and edit developer documentation for SDKs, libraries, and frameworks, including sites such as ai-sdk.dev and chat-sdk.dev. Use for getting-started guides, tutorials, API references, conceptual explanations, integration guides, migration guides, troubleshooting, and code examples.

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。

Audit a website's SEO with Firecrawl. Use when the user asks for an SEO audit, metadata and heading review, sitemap/site-structure analysis, keyword opportunities, competitor SERP comparison, or prioritized search optimization recommendations.

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 products across the web with Firecrawl and produce a shopping recommendation or cart-ready summary. Use when the user wants to compare products, find the best option, evaluate reviews, respect budget/preferences, or shop with a saved browser session.

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 outcome-focused Firecrawl workflows that produce deliverables such as research reports, literature reviews over published papers, SEO audits, QA reports, lead lists, knowledge bases, website design systems, and other structured web-data artifacts. Use when the user wants Firecrawl to complete a business, marketing, product, or creative workflow rather than merely scrape a page or integrate API calls into 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。

Produce pre-meeting lead intelligence briefs with Firecrawl. Use when the user needs company research, person research, recent news, talking points, pain points, or outreach preparation before a sales call, partnership meeting, investor conversation, or customer interview.

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。

QA test a live website with Firecrawl browser and scrape evidence. Use when the user wants exploratory QA, form testing, navigation/link checks, responsive checks, performance observations, bug reports, or a pre-launch quality review.

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。

Refine rendered finish at accepted viewports.

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。

Animate routes; support native View Transitions.

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。

Resolve motion tools or native View Transitions.

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。

Repair interchangeable website design patterns.

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。

Review trust before frontend tooling adoption.

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。

Review whole motion-system release resilience.

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 redundant or unsupported page content.

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-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.

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 whenever reasoning about immunology, host-pathogen interactions, innate immunity, Toll-like receptors (TLRs), or experimental design in molecular biology. It is also highly relevant for scientific career strategy, particularly when discussing independence, pivoting research domains, or using reverse genetics (like knockout mice) for discovery. Channel Shizuo Akira, immunologist and pioneer of pattern-recognition receptors, to apply rigorous experimental standards (e.g., demanding chemically synthesized mimics over purified extracts) and to view innate immunity as a highly specific, compartmentalized system rather than a primitive defense.

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。

Applies the reasoning style of Kaiming He, computer vision pioneer and creator of ResNet. Use this skill whenever you are designing deep learning architectures, debugging neural network optimization, formulating generative AI problems, or bridging AI with other scientific domains. Trigger this skill for discussions on network depth, weight initialization, residual learning, flow matching, or when reframing discriminative tasks as conditional generation. It emphasizes simplicity in complex visual problems, end-to-end optimization, and viewing AI as a universal language for science.

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。