「event」の検索結果

Secure LLM-powered applications with input validation, output controls, tenant isolation, and abuse prevention.

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。

Handle security incidents with IR playbooks and procedures. Implement detection, containment, eradication, and recovery processes. Use when responding to security events or building incident response capabilities.

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。

Configure AWS CloudTrail for audit logging. Set up organization trails and event analysis. Use when auditing AWS activity.

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Build AI-focused SRE incident response practices for LLM outages, degraded quality, runaway cost events, and safety 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 WeChat Mini Program AI via wx.cloud.extend.AI (小程序, wx.cloud apps). Covers generateText and streamText with callbacks (onText, onEvent, onFinish); streamText needs a data wrapper, generateText returns the raw response. Models via wx.cloud.extend.AI.createModel with groups hunyuan-exp (小程序成长计划), cloudbase (main managed), or custom-*; model id goes in the data wrapper `model` field. MUST run two-step preflight before code — see body. NOT for browser/Web (use ai-model-web), Node.js backend (use ai-model-nodejs), or image generation (use ai-model-nodejs).

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CloudBase function runtime guide for building, deploying, and debugging your own Event Functions or HTTP Functions. This skill should be used when users need application runtime code on CloudBase, not when they are merely calling CloudBase official platform APIs.

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Build and deploy AI agents with CloudBase Agent SDK (TypeScript & Python). Implements the AG-UI protocol for streaming agent-UI communication. Use when deploying agent servers, using LangGraph/LangChain/CrewAI adapters, building custom adapters, understanding AG-UI protocol events, or building web/mini-program UI clients. Supports both TypeScript (@cloudbase/agent-server) and Python (cloudbase-agent-server via FastAPI).

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Compile a weekly productivity report using Agent Monitor data — daily_sessions and daily_events trends, per-session costs from pricing engine, token volumes (input/output/cache_read/cache_write + baselines), tool usage top 20, session completion rates by status, and workflow intelligence metrics.

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。

Scan recent Claude Code activity for errors and failure signals across all sessions using Agent Monitor data — APIError events and PreToolUse→PostToolUse gaps (tools that started but never completed) — then group failures by tool and model and rank them by frequency. Use when checking for errors or asking "what's failing right now".

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Trace error propagation through a multi-agent session by agent depth — where failures originated, the depth at which they appeared, and how they cascaded up to parent agents — using the Agent Monitor workflow intelligence API and the session event stream. Use when a multi-agent run failed and you need to find the origin and blast radius of the failure.

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Generate a CCAM reliability report from session outcomes, hook events, alerts, tool failures, and data freshness. Use for health reviews, incident follow-up, hook-delivery audits, or reliability trend summaries.

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 daily standup summary from recent Claude Code sessions — completed work grouped by project (cwd), session costs from the pricing engine, tool invocations, error/compaction/APIError events, and turn velocity metrics from session metadata (turn_count, total_turn_duration_ms).

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Detect quality and efficiency regressions over time using Agent Monitor data — rising error rate (APIError events), falling cache hit rate, growing compaction frequency, and climbing cost-per-session. Splits history into an earlier baseline window and a recent window and reports which metrics are getting worse, by how much, and where. Use when checking whether things are degrading or trending in the wrong direction.

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Suggest concrete optimizations for Claude Code usage based on historical session data. Covers cost reduction, speed improvement, error prevention, and workflow efficiency. Use for data-driven optimization planning.

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Compile a month-over-month retrospective from Agent Monitor data — sessions, cost, token volumes, completion rate, top projects by working directory, and notable shifts versus the prior month. Uses daily_sessions/daily_events (365d) from analytics, the session list, and the pricing cost breakdown. Use when doing a monthly retrospective or planning the month ahead.

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 comprehensive session report with per-model token usage (input, output, cache_read, cache_write including compaction baselines), cost breakdown via the pricing engine, tool invocations, agent hierarchy, compaction events, API errors, turn durations, and thinking block counts. Use when reviewing a specific session or summarizing activity over a date range.

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Inspect fired CCAM alerts and manage alert rules for token thresholds, event patterns, inactivity, and status duration. Use when acknowledging alerts, creating or editing a rule, checking cooldowns, or connecting alert rules to webhook targets.

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Polls the Agent Monitor /api/stats endpoint several times over a short window and reports the live deltas in active_sessions, active_agents, events_today, and ws_connections so you can see activity moving in real time. Use when watching the dashboard for live changes rather than a one-time snapshot.

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Export Claude Code session and analytics data in JSON, CSV, or Markdown formats. Supports exporting sessions, events, costs, and analytics for external analysis or reporting. Use for data backup or integration.

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 anomalous sessions using Agent Monitor data — cost outliers from the pricing engine, token anomalies (cache miss spikes, compaction baseline surges), unusual event type ratios (PreToolUse/PostToolUse gaps, APIError clusters), behavioral deviations from workflow intelligence (complexity score outliers, error propagation anomalies), and sessions with abnormal metadata (extreme turn_count, high thinking_blocks, zero turn_duration).

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React 19 performance patterns and composition architecture for Vite + Cloudflare projects. 50+ rules ranked by impact — eliminating waterfalls, bundle optimisation, re-render prevention, composition over boolean props, server/client boundaries, and React 19 APIs. Use when writing, reviewing, or refactoring React components. Triggers: 'react patterns', 'react review', 'react performance', 'optimise components', 'react best practices', 'composition patterns', 'why is it slow', 'reduce re-renders', 'fix waterfall'.

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Comprehensive skill for Locomotive Scroll smooth scrolling library with parallax effects, viewport detection, and scroll-driven animations. Use this skill when implementing smooth scrolling experiences, creating parallax effects, building scroll-triggered animations, or developing immersive scrolling websites. Triggers on tasks involving Locomotive Scroll, smooth scrolling, parallax, scroll detection, scroll events, sticky elements, horizontal scrolling, or GSAP ScrollTrigger integration. Integrates with GSAP for advanced scroll-driven animations.

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RenderDoc GPU frame-capture analysis — headless .rdc capture, batch deserialization, frame reports and full-text search scripts, plus the manual Event Browser / Pipeline State / shader-debug workflow. Use when an image is wrong (missing, black, NaN, wrong color, flickering), when pipeline state or resource contents need ground truth, or when a frame looks slow.

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When the user wants to reduce churn, improve customer retention, or plan lifecycle marketing. Also use when the user mentions "retention," "churn," "customer lifecycle," "churn prevention," "at-risk customers," or "loyalty program." For lifecycle, use growth-funnel.

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。