2,235 件 ・ 関連度順
概要と使いどころ
Complete community building, engagement, and monetization system. From zero to thriving community — launch strategy, member engagement loops, content programming, moderation frameworks, growth tactics, monetization models, and health metrics. Works for Discord, Slack, Telegram, Circle, forums, or any platform.
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 and implement adaptive testing systems using Item Response Theory (IRT). Use when working with computerized adaptive tests (CAT), psychometric assessment, ability estimation, question calibration, test design, or IRT models (1PL/2PL/3PL). Covers test algorithms, stopping rules, item selection strategies, and practical implementation patterns for K-12, certification, placement, and diagnostic assessments.
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。
Plan, prioritize, and design rigorous A/B tests using the Test Velocity Method. Use when a user wants to test a landing page, CTA, email, signup flow, pricing page, or any digital experience — this skill produces a complete, dev-ready test plan with hypothesis, sample size, duration, segmentation strategy, and guardrail 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。
Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution 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。
获取并生成 A股单只股票的关键指标“体检卡”（估值/盈利质量/现金流/负债/分红/交易活跃度等），输出为统一 Markdown，便于对比与持续跟踪。用在："帮我查600406关键指标"、"做一张国电南瑞体检卡"。
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。
Add or review dygo Logs, Activity, Audit Logs, health checks, diagnostics, metrics, traces, and operator-visible failure states. Use when runtime behavior must become inspectable or diagnosable.
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。
Automate SEO research with Ahrefs -- analyze backlink profiles, research keywords, track domain metrics history, audit organic rankings, and perform batch URL analysis through the Composio Ahrefs 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。
Debug LangChain and LangGraph agents by fetching execution traces from LangSmith. Analyze agent behavior, investigate errors, and review tool calls and performance 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。
Datadog CLI for searching logs, querying metrics, tracing requests, and managing dashboards. Use this when debugging production issues or working with Datadog observability.
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 applications with Azure Application Insights and OpenTelemetry for end-to-end observability. Use this skill when users ask about telemetry, tracing, metrics, logging, or monitoring setup. Covers SDK setup, correlation, sampling, dashboards, and alerts per OpenTelemetry standards.
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。
Diagnose Azure application and infrastructure issues with a structured, evidence-based workflow. Use this skill when users ask to troubleshoot outages, latency, failures, configuration drift, or anomalies. Root cause analysis using logs, metrics, traces, and dependency mapping.
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。
Auto-activate for litestar_granian, GranianPlugin, litestar run Granian options, runtime threads, HTTP/2, TLS, access logs, metrics, static mounts, or worker lifecycle. Not for non-Granian servers.
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。
研究評価指標（論文数、被引用数、h-index等）の収集・分析を行う
Weekly engineering retrospective from commit history, work patterns, and code-quality metrics, with trend tracking and per-person breakdown. NOT for per-session reflection (mk:memory / Phase 6).
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。
Autonomously improve one measurable metric via bounded, git-tracked iterations: one scoped change, verify, keep or revert. NOT for cleanup (mk:cook), known-cause bugs (mk:fix), or shipping (mk:ship).
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。
Weekly-cadence engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware: breaks down per-person contributions with praise and growth areas. Use when asked to "weekly retro", "what did we ship", or "engineering retrospective". Proactively suggest at the end of a work week or sprint. NOT for per-session or per-task reflection (see mk:memory / Phase 6 Reflect).
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。
Turn a raw idea into ONE honest recommendation: interview one question at a time until the problem, requirements, goals, non-goals, and constraints are CONFIRMED, then deliver a single verdict — do, don't, cheaper alternatives, trade-offs, ordered checklist, success metrics. Required: the user wants exactly ONE recommendation — not options, not a debate — and their framing is open to challenge (advise may answer a different question than the one asked). Triggers on "what should I do about X", "advise me on X", "am I approaching this right", "is this the right move". Do NOT use to be interrogated with no recommendation (→ mk:grill) — advise also interviews one question at a time, but only to reach a verdict. Do NOT use when the framing is settled and only the options are open (→ mk:brainstorming). Do NOT use to decide whether something is worth building (→ mk:office-hours). Do NOT use when you want several perspectives to argue it out (→ mk:party).
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。
Analyze bundle size and performance 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。
Quantitative agent evaluation using 4-metric framework (correctness/step_ratio/tool_call_ratio/latency_ratio) with ideal trajectory annotation and capability-categorical taxonomy. Use when measuring agent efficiency, comparing agent variants, or gating new agents through correctness→efficiency phases. Complements harness-eval (SE benchmarks) and evaluator-optimizer (qualitative rubric).
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。
Deterministically score comparable imported review-run lanes with root-cause metrics and uncertainty. Use only when the user explicitly asks to benchmark normalized local review runs or use the bundled synthetic fixture.
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 approved Grafana business-intelligence evidence for revenue, conversion, and operational KPIs. Use for bounded KPI scorecards, financial or operational metric checks, baseline comparisons, and business-unit reviews without changing source systems.
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。
Designs the first screen visitors see — the hero section. Layout patterns (split, centered, asymmetric, full-bleed), navbar design, headline typography, CTAs, background treatments (gradients, video, particles, 3D), scroll cues, and above-the-fold conversion strategy. Activate on 'hero section', 'landing page hero', 'above the fold', 'first impression', 'homepage header', 'navbar design', 'hero layout', 'landing page design'. NOT for full multi-page site architecture (use web-design-expert), not for SEO content strategy (use seo-visibility-expert).
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。
Holistic evaluation framework for language models measuring accuracy, calibration, robustness, and fairness
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 face recognition systems with InsightFace, ArcFace, enrollment pipelines, HDBSCAN clustering, and privacy-compliant architecture. Activate on: face recognition, face enrollment, face clustering, identity verification, facial search. NOT for: general object detection (computer-vision-pipeline), emotion analysis (ai-engineer).
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。