「aces」の検索結果

Make a repository Superset-ready by authoring .superset/config.json with setup, teardown, and run scripts so every new workspace boots configured, then verifying with a real workspace. Use when the user wants to set up a project or repo for Superset, configure workspace setup scripts, or fix a failing workspace setup ("new workspaces don't have node_modules", "my .env is missing in workspaces", "setup script isn't running").

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 Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected to the HF MCP server.

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 and fix issues from Sentry using MCP. Use when asked to fix Sentry errors, debug production issues, investigate exceptions, or resolve bugs reported in Sentry. Methodically analyzes stack traces, breadcrumbs, traces, and context to identify root causes.

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。

Guides Stripe integration decisions — API selection (Checkout Sessions vs PaymentIntents), Connect platform setup (Accounts v2, controller properties), billing/subscriptions, Treasury financial accounts, integration surfaces (Checkout, Payment Element), and migrating from deprecated Stripe APIs. Use when building, modifying, or reviewing any Stripe integration — including accepting payments, building marketplaces, integrating Stripe, processing payments, setting up subscriptions, or creating connected accounts.

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 dark-mode glassmorphism interfaces with readable contrast, frosted surfaces, and gradient borders using a pseudo-element mask. Use when asked for glass cards, frosted dark hero sections, blur panels, or dark UI systems with gradient/glow borders.

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。

Apply subtle gradient-border treatments for premium web surfaces. Use when cards, pricing panels, nav bars, modals, buttons, or hero surfaces need a refined edge highlight without a loud glow.

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。

Draws true-isometric diorama illustrations of developer and design workspaces in one green ramp, generated as SVG with a bundled scene kit. Traits: one rounded off-white slab with a faceted bevelled edge; every face filled by the way it faces (top lightest, right darkest) from five greens; 0.9 deep-green outlines on every edge; dense fine repeated detail (rack units, ribs, vents, keys, code lines); soft green shadows and glows on the slab. Covers projection, shading, line weights, object vocabulary, layout and the iso.mjs kit (racks, databases, laptops, containers, cards, badges, books, plants, cables, status tower). Use when someone asks for isometric illustration, an iso scene, 2.5D tech art, monochrome or green isometric art, a server room, dev stack or cloud picture, or art for empty states, onboarding, 404 pages, blog headers, feature spots or marketing cards in this style.

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 the cmux macOS terminal app: workspaces, panes, surfaces, browsers, notifications, settings, and hooks. Use only when the user explicitly names cmux. Read before running any cmux command.

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Taking a multi-PR feature from "shape unknown" to merged without five review rounds per PR: spike until interfaces stop moving, write the contract, cut PRs along contract seams, one review per PR. Use when starting a feature that touches more than one lifecycle object or public interface, when a PR review keeps changing interfaces, or when splitting a large branch.

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。

Problem-solving strategies for hilbert spaces in functional analysis

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Problem-solving strategies for vector spaces in linear algebra

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Problem-solving strategies for banach spaces in functional analysis

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Analyze Chrome, Chromium, Electron, React DevTools, or Perfetto-compatible JSON traces and audit user-reported profiling findings without loading large artifacts into context; prove trigger-to-render/layout chains, separate measured facts from source inference, find exact code choke points, classify forced layout and render fanout, implement semantically safe fixes, and verify behavior plus repository budgets. Use for trace files, reported profiling durations or call chains, dropped frames, long tasks, resize or scroll jank, render storms, layout thrashing, selector hot paths, interaction latency, or requests to locate exact source-level bottlenecks.

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。

List active GSD workspaces and their status

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。

[omh] Turn repeated lessons into written rules: extract repeated principles from skills, prompts, traces, reviews, and failures into reviewed rule candidates without auto-mutating guidance. Use when the user says: rules-distill, rules distill, distill rules, rule distillation, principle distill, skill principles, extract agent rules, turn traces into rules.

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。

Real-world mimicry with textured surfaces, 3D effects, and familiar physical metaphors for intuitive digital interfaces.

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。

Smooth color transitions and gradient-rich surfaces for modern, playful interfaces with visual depth.

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。

Instrument browser/web apps with the Application Insights JavaScript SDK (@microsoft/applicationinsights-web). Use for Real User Monitoring (RUM) — page views, clicks, AJAX/fetch dependencies, exceptions, custom events, and browser-side GenAI agent traces correlated to backend OpenTelemetry traces. Covers SDK Loader Script and npm setup, framework extensions (React, React Native, Angular), Click Analytics, telemetry initializers, and OTel GenAI semantic conventions for agent/tool/model spans emitted from the browser.

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 asks to "figure out where our direct traffic really comes from", "measure dark social", "add a how-did-you-hear-about-us field", or "show social drives signups without click data"; produces a share-link/UTM hygiene spec for owned share surfaces, a self-reported attribution field design that replaces an existing form field (free-text first, coded later), a GA4 direct-traffic decomposition read (deep-URL directs, mobile-app skew, private-push correlation) with every derived number hard-labeled Estimated/proxy, and a branded-search-lift proxy from GSC plus Wikipedia pageviews — the declared dark-social method behind ECHO O2. Not for paid-channel attribution reconciliation (platform-claimed vs analytics conversions) — use attribution-reconciler. 暗社交归因/直接流量分解/自报来源字段/分享链路UTM

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 asks to "map what our surfaces say today", "inventory our current messaging", or "find the gap between what we say and what we mean"; produces the narrative baseline — a surface-by-surface inventory of what every owned touchpoint (homepage, pricing, docs, decks, social bios, email footers) claims RIGHT NOW, each line labeled Measured / User-provided / Estimated, plus a per-surface gap read vs the intended message and the drift-baseline snapshot the Evaluate phase measures future drift against. Not for authoring the canon — use message-system-architect; not for scoring the surfaces or running the vetoes — use narrative-quality-auditor. 现状叙事盘点/各触点口径/意图差距/漂移基线

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。

Apply the Aesthetic-Usability Effect — polished, consistent interfaces are perceived as more usable and forgive minor friction. Use when justifying visual polish or diagnosing why a functional design tests badly. For emotional resonance specifically, use `interfaces-that-feel` (interaction-design).

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。

Coordinate the AWS DevOps Agent across multiple AgentSpaces from one Claude Code session — route questions to the right space (prod vs staging vs knowledge), query several spaces in parallel and synthesize, or compare findings across accounts. Use whenever the user has more than one AgentSpace configured, mentions multiple AWS accounts, or asks something like "check both prod and staging", "compare across accounts", or "ask the knowledge space".

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Use when your agent or environment is broken — wrong answers, errors, timeouts, tool failures, or CLI issues. Reads traces and logs to diagnose root causes. Also checks prerequisites when the CLI itself isn't working. Triggers on: "agent not working", "wrong answer", "agent error", "tool call failing", "debug agent", "check logs", "read traces", "broken", "500 error", "424 error", "model access denied", "command not found", "stuck in DELETING", "maxVms exceeded", "cold start diagnosis", "cold start slow", "agentcore create error", "create failed", "exit code 7", "connection refused local dev". Not for deploy failures — use agents-deploy. Not for performance tuning without errors — use agents-optimize. Not for VPC configuration — use agents-build. Not for observability setup or missing logs — use agents-optimize.

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, configures, debugs, and optimizes AWS observability - operator-symptom questions and detecting Omni vs classic CloudWatch. CloudWatch on an already-reporting service: Log Insights, metric/composite/anomaly alarms, custom metrics/EMF, dashboards, X-Ray/ADOT tracing, canaries, CloudTrail, Dynamic Instrumentation (live breakpoints/snapshots), the Application Signals service map, and fleet health views. CloudWatch Omni on an existing Space: SQL over logs and traces, PromQL over metrics, Omni dashboards, Omni alerts, context graph for root cause, programmatic/IaC access (API/SDK/CLI/CloudFormation), driving Omni from a coding agent or skills, and evaluating AI agent quality from traces - on-demand and online scoring of live traffic, readback, custom evaluators. For first-time setup - creating an Omni Space, granting access, ingestion, or ADOT instrumentation for Application Signals (ServiceEvents, CI/CD metadata) or Omni - use setting-up-cloudwatch-observability. Not for app logging or threat 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。