245 件 ・ 関連度順
概要と使いどころ
Build a reporting pipeline — scheduled reports with SQL queries, delivery via Slack or email, threshold alerts, and historical comparison. Use when asked for "automated reports", "scheduled report", "email digest", or "Slack alerts for 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。
Analyzing patterns of continuity and change over time in historical contexts. Covers periodization (how and why we divide history into eras), identifying turning points, measuring rates of change, and recognizing long-term patterns and trends. Use when analyzing temporal structure in history, debating period boundaries, or assessing whether a moment represents genuine transformation or surface-level disruption.
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。
Distributional analysis of environmental benefits and burdens across communities. Covers the historical origins of environmental justice in the U.S. civil rights tradition, siting and exposure disparities, indigenous rights and land stewardship, climate justice at global and intergenerational scales, procedural vs. distributional vs. recognition justice, and the environmental justice screening tools used by regulators. Use when analyzing who bears environmental harm and who receives environmental benefit, or when designing interventions whose distributional consequences matter.
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。
OpenStack capacity planning operations skill for resource planning, quota management, and scaling decisions. Covers compute capacity (allocation ratios, vCPU/RAM utilization, host aggregates, availability zones), storage capacity (Cinder pool sizing, thin provisioning, Glance storage, Swift rings), network capacity (floating IP pools, port quotas, subnet sizing), project quota management (templates for small/medium/large profiles), flavor sizing strategy, utilization analysis with placement service, growth forecasting from historical metrics, and right-sizing recommendations for underutilized resources.
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。
OpenStack monitoring operations skill for deploying, configuring, and operating the cloud health monitoring stack. Covers Prometheus metric collection and scrape targets, Grafana dashboard provisioning and visualization, Alertmanager notification channels and routing, alerting rules for service health and resource exhaustion, service endpoint health checks, log aggregation strategies, SLA tracking with availability and response time percentiles, and capacity trend analysis from historical metrics. Use when deploying monitoring via Kolla-Ansible, configuring alert thresholds, troubleshooting blank dashboards, tuning noisy alerts, or analyzing cloud performance trends.
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。
Track and analyze US government shutdown liquidity impacts by monitoring TGA (Treasury General Account), bank reserves, EFFR, and SOFR data from FRED API. Use when user wants to (1) analyze current or past government shutdown effects on financial markets, (2) track liquidity conditions during fiscal policy disruptions, (3) assess "stealth tightening" effects, (4) compare shutdown episodes across different monetary policy regimes (QE vs QT), or (5) generate liquidity stress reports with historical context. Recommended usage frequency is weekly on Wednesdays after TGA/reserve data releases.
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。
Triages AWS CloudWatch alarms using the CloudWatch DescribeAlarms API, GetMetricData for historical analysis, and CloudTrail LookupEvents for root cause correlation. Prioritizes alerts by blast radius and provides remediation playbooks.
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。
Assesses underlying asset pools with stratification, concentration analysis, historical performance, and credit quality distribution. Use when analyzing collateral pools, stratifying asset characteristics, or evaluating pool quality.
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。
Maps institutional investor targeting with AUM analysis, sector allocation preferences, and historical participation patterns. Use when targeting investors, analyzing demand profiles, or building investor marketing lists.
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。
Evaluates fraudulent conveyance risk for leveraged transactions with solvency analysis and reasonably equivalent value assessment. Use when analyzing fraudulent transfer risk, conducting solvency tests, or evaluating historical transactions.
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。
Evaluates insider purchase patterns with cluster buying identification, historical signal analysis, and conviction scoring. Use when analyzing insider buying, assessing management confidence signals, or tracking insider activity 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。
Source pre-2016 cinema with gothic/occult sensibility, literary texture, and historical grandeur — build watchlists, curate Criterion/MUBI picks. Uses Perplexity for film discourse, Exa for web search, Firecrawl for scraping. Triggers on film recommendations, watchlist, gothic cinema, occult film, arthouse, pre-2016 movies.
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。
Perform capacity planning using historical metrics and growth models. Use predict_linear for forecasting, identify resource constraints, calculate headroom, and recommend scaling actions before saturation. Use before seasonal traffic spikes or product launches, during quarterly capacity reviews, when resource utilization trends upward, or before budget planning cycles.
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 polychromatic ornamental patterns grounded in Alexander Speltz's classical ornament taxonomy. Builds on monochrome structural analysis by adding period-authentic color palettes, color-to-motif mapping, and rendering styles suited to painted, illuminated, and glazed ornament. Use when creating decorative designs where color is integral to the tradition (Islamic tilework, illuminated manuscripts, Art Nouveau), exploring how historical periods used color in ornament, or producing colored reference imagery for design, illustration, or educational materials.
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。
Select an OCR/HTR engine by benchmarking candidates on the same labelled samples — source ground truth from open datasets (e.g. Hugging Face PAGE-XML corpora) or hand-transcription, wrap every engine behind a transcribe(image_path) -> str adapter (vision-LLMs via any OpenAI-compatible endpoint, dedicated HTR REST APIs, cloud OCR), and score with zero-dependency raw CER, lenient CER, WER, and a critical name/date token diff. Use when choosing an engine for handwriting or historical-document transcription, when published accuracy claims need honest verification on your own material, or when a records workflow must surface confident-but-wrong names and dates that a low aggregate CER hides.
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。
Operator-side analysis of historical ML experiment PRs in Senpai research tracks. Use this skill whenever the user asks to: analyze experiments, categorize PRs, bucket experiments, summarize what's been tried, understand experiment history, review merged vs closed results, or asks "what experiments have we run / worked / failed". Also triggers for: "pull the latest experiments", "what's been tried so far", "category breakdown of PRs", "which experiments succeeded", "noam track analysis". When a branch name is mentioned (e.g. "noam branch", "on the noam branch"), pass it as the base branch to scope the fetch to just those PRs.
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。
Operator-side guide for generating a target-specific training curve chart for a legacy experiment PR. Use when auditing or presenting historical runs.
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。
Testing Angular 18-21: TestBed, component harnesses (@angular/cdk/testing), Karma+Jasmine (default historical) vs Jest (jest-preset-angular, modern), Angular Testing Library (RTL-style). HttpClient mocking via HttpTestingController. NgRx Effects testing. Cypress / Playwright e2e. Use this skill to: - Detect runner (Karma+Jasmine vs Jest) and configure correctly. - Write component tests with TestBed. - Use component harnesses for Material / custom UI components. - Mock HttpClient via provideHttpClientTesting + HttpTestingController. - Test signal-based inputs with componentRef.setInput(). - Test NgRx Effects with provideMockActions. Do NOT use this skill for: - General Angular conventions (see angular-conventions). - Routing patterns broadly (see angular-routing — covers testing routes briefly). - Form patterns broadly (see angular-forms).
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 one prepared Agent evidence packet as an additive Issue comment, including historical or closed Issues, under exact current authorization. Use after read-only Issue inspection and separately authorized evidence preparation. Do not reproduce, select work, upload assets, edit human text, claim, review, close, or change Issue metadata.
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。
Risk Assessment & Position Sizing — volatility profile (beta/ATR/HV), historical drawdowns, correlation analysis, liquidity risk, position sizing tables (fixed %, volatility-adjusted, Kelly Criterion), and VaR estimates. Returns Risk Score (0-100, higher = safer). Triggered by "trade risk <TICKER>".
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。
Content angle generator for turning dry expert topics into high-engagement infotainment. Applies 7 journalistic angle types (Myth vs Reality, Paradox, Level Error, Price of Solution, Conditions, Hidden Driver, Contrary Thesis) + historical/future lens + news-hook framing. Use when experts need their content to become interesting rather than just informative - blog posts, video scripts, social content, newsletters, landing pages, ad hooks. For any niche: B2B, B2C, services, products, personal brand.
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 documenting a named campaign across time and victims, the user asks to start or update a campaign record, or another skill identified a multi-incident cluster that warrants formal tracking. Provides the template (timeline, attribution, victimology, attack chain, Diamond Model mapping, IOC clusters) and the lifecycle from active to historical.
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。
Develops comprehensive threat actor profiles for APT groups, criminal organizations, and hacktivist collectives by aggregating TTP documentation, historical campaign data, tooling fingerprints, and attribution indicators from multiple intelligence sources. Use when briefing executives on sector-specific threats, updating threat model assumptions, or prioritizing defensive controls against specific adversaries. Activates for requests involving MITRE ATT&CK Groups, Mandiant APT profiles, CrowdStrike adversary naming, or sector-specific threat briefings.
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 historical VS Code GitHub Copilot Chat sessions by model, reasoning effort, AIU, time, reliability, workflow behavior, and external quality evidence, or safely prune workspace-scoped local chat history by age. Use for session analysis, repeated-task retrospectives, model evaluation, cost/performance analysis, and old session cleanup.
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。