「store」の検索結果

Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases.

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。

When the user wants to monitor, triage, or reduce their app's crash rate — including setting up Crashlytics, prioritizing which crashes to fix first, interpreting crash data, and understanding how crashes affect App Store ranking. Use when the user mentions "crash", "crashlytics", "crash rate", "ANR", "app not responding", "crash-free sessions", "crash-free users", "symbolication", "stability", "firebase crashes", "app crashing", or "crash report". For overall analytics setup, see app-analytics.

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。

When the user wants to discover, evaluate, or prioritize App Store keywords. Also use when the user mentions "keyword research", "find keywords", "search volume", "keyword difficulty", "keyword ideas", or "what keywords should I target". For implementing keywords into metadata, see metadata-optimization. For auditing current keyword performance, see aso-audit.

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。

When the user wants to improve their app's star rating, increase ratings volume, optimize when and how they prompt users for a review, or recover from a bad rating period. Use when the user mentions "app rating", "star rating", "review prompt", "SKStoreReviewRequest", "In-App Review API", "ask for review", "low rating", "rating drop", "get more reviews", or "recover from 1-star". For responding to reviews, see review-management. For overall ASO health, see aso-audit.

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。

When the user's app or update was rejected by Apple App Review or Google Play Review and they need to diagnose why, fix it, and resubmit fast. Use when the user mentions "app rejected", "App Review rejection", "guideline violation", "Apple rejected my app", "Google Play rejected", "Play policy violation", "Resolution Center", "metadata rejection", "binary rejection", "guideline 2.1", "guideline 4.3", "guideline 5.1.1", "Sign in with Apple required", "Apple ID rejection", "Play Store suspension", "appeal", "I need to respond to App Review", or "expedited review". For pre-submission listing health, see aso-audit. For metadata-only fixes, see metadata-optimization.

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。

When the user wants to get press coverage, media mentions, or editorial features for their app — including writing press releases, pitching journalists, getting on "best apps" lists, or building an app press kit. Use when the user mentions "press", "PR", "media coverage", "TechCrunch", "journalist", "press release", "app press kit", "get featured in media", "editorial coverage", "review from a blogger", or "app launch announcement". For Apple editorial featuring, see app-store-featured. For launch strategy, see app-launch.

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。

When the user wants to optimize their App Store listing for seasonal events, holidays, or trending moments — including keyword opportunities, metadata updates, screenshot theming, and timing strategy. Use when the user mentions "seasonal", "holiday", "Christmas", "New Year", "Valentine's Day", "summer", "back to school", "seasonal keywords", "trending now", "limited time", or wants to capitalize on a calendar event. For general keyword research, see keyword-research. For full metadata rewrites, see metadata-optimization.

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。

When the user wants to track App Store chart rank changes, find top gainers and losers, detect breakout apps entering the top 100, or identify apps dropping out of charts. Also use when the user mentions "chart movers", "rank changes", "who's rising", "who's falling", "new chart entries", "top gainers", or "market shifts". For broader market overview, see market-pulse. For competitive keyword analysis, see competitor-analysis.

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。

When the user wants to localize their App Store listing for international markets. Also use when the user mentions "localization", "translate my app", "international markets", "expand to new countries", "localize metadata", or "which countries should I target". For keyword research in specific markets, see keyword-research. For metadata writing, see metadata-optimization.

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。

When the user wants to optimize App Store metadata — title, subtitle, keyword field, or description. Also use when the user mentions "optimize my title", "ASO metadata", "keyword field", "character limits", "app description", or "write my subtitle". For keyword discovery, see keyword-research. For full ASO audits, see aso-audit.

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。

When the user wants to analyze competitors' App Store strategy, find keyword gaps, or understand competitive positioning. Also use when the user mentions "competitor analysis", "competitive research", "keyword gap", "what are my competitors doing", or "compare my app to". For keyword-specific research, see keyword-research. For metadata writing, see metadata-optimization.

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 the native (MSIX, isolated-session) OpenClaw Gateway from the latest openclaw/openclaw sources (or any ref, local checkout, or prebuilt openclaw.tgz), register it side by side with the Microsoft Store Gateway, and run Companion against it with OPENCLAW_NATIVE_GATEWAY_DEV_PATCH. Use when the user asks to test Companion with Gateway main, an unreleased Gateway change, or a source-built native Gateway, or to remove such a build.

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。

On-demand provisioning guide for a Memmy GUI task that fully connects an explicitly named local Agent: discover its active history store, install or remove its rendered Memmy Skill, bootstrap a scan boundary, persist a validated automatic-sync recipe, and verify GUI-visible readiness.

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。

Owns data as an asset — governance, quality, the warehouse and semantic layer, analytics capability, and the governance of models built on top. Use this for a decision about how data is collected, stored, defined, or shared; when numbers disagree between teams; when deciding what to build in-house versus buy; when standing up a data function; or when an AI or model decision needs governance rather than engineering.

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。

Submit a GitHub repository to be indexed by the OpenAkita Skill Store. Use when user wants to share their skills repo with the community.

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。

Publish a local Agent to the OpenAkita Platform Agent Store. Package and prepare a local Agent for publishing to the community hub.

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。

Control deep thinking mode. Default enabled. For very simple tasks (simple reminders, greetings, quick queries), can temporarily disable to speed up response. Auto-restores to enabled after completion.

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。

Search for Agents on the OpenAkita Platform Agent Store

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。

Window management operations. When you need to list all open windows, switch to a specific window, minimize/maximize/restore windows, or close windows. Use title parameter for targeting specific window (fuzzy match).

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。

Download and install an Agent from the OpenAkita Platform Agent Store

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。

Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Use this skill whenever the user mentions changelogs, release notes, version updates, "what changed", product updates, app store descriptions, or needs to summarize recent development work for non-technical audiences.

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。

Re-enable the skill bus after pausing. Restores subscription processing.

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 when the user asks about Stripe Connect configuration, charge patterns, Dashboard access, or how to get started with Connect, is building a marketplace, platform, multi-vendor store, gig platform, or subscription platform, needs to pay out sellers, vendors, or providers, mentions split payments, revenue sharing, multi-party payments, or similar payment distribution concepts, provides a company URL or business description for a recommendation, builds SaaS that routes money between parties (for example, POS, booking, invoicing — not operational SaaS without payment routing), asks about onboarding or KYC for merchants, sellers, and vendors, mentions connected account Dashboard or responsibility configurations, or asks about payment flows, white-label payments, or embedded payments.

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 when writing analytical SQL over time-series data with the TimescaleDB Toolkit (timescaledb_toolkit extension) hyperfunctions: approximate percentiles, statistical summaries, time-weighted averages, counter/gauge rates, uptime/heartbeat tracking, state durations, OHLC candlesticks, approximate distinct counts, top-N, and downsampling. **Trigger when user asks to:** - Compute percentiles/medians/p95/p99 over large or rolled-up time-series data - Compute rates or deltas from monotonic counters (Prometheus-style) or gauges - Compute time-weighted averages or integrals over irregularly sampled data - Track uptime/downtime from heartbeats, or time spent in each state - Build OHLC/candlestick or VWAP data for financial ticks - Store re-aggregatable summaries in continuous aggregates (two-step aggregation, rollup) - Approximate COUNT DISTINCT, find top-N / most frequent values, or downsample for charts **Keywords:** timescaledb_toolkit, hyperfunctions, percentile_agg, uddsketch, tdigest, approx_percentile, stats_agg, time_weight, counter_agg, gauge_agg, heartbeat_agg, state_agg, candlestick_agg, hyperloglog, approx_count_distinct, min_n, max_n, mcv_agg, lttb, asap_smooth, rollup, two-step aggregation

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。