「pattern」の検索結果

Use when working with Clerk — clerk authentication and user management platform covering users, sessions, organizations, invitations, and sign-in methods. Use when analyzing user growth, monitoring authentication health, reviewing organization membership, managing Clerk users, or auditing sign-in 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。

Use when working with Bigpanda — bigPanda AIOps platform management covering event correlation, root cause analysis, incident management, alert enrichment, topology-based correlation, environment management, and analytics. Use when configuring BigPanda correlation patterns, investigating correlated incidents, tuning noise reduction, or analyzing alert topology and root cause indicators.

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 working with Caddy — caddy web server management, automatic TLS certificate handling, reverse proxy configuration, site management, and plugin inspection. Covers Caddyfile analysis, admin API usage, access logs, and upstream health monitoring. Read this skill before any Caddy operations — it enforces discovery-first patterns, anti-hallucination rules, and safety constraints.

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 working with Azure Entra — azure Entra ID (formerly Azure AD) management for user lifecycle, app registrations, service principals, conditional access policies, sign-in log analysis, and directory role assignments. Covers B2B guest users, enterprise applications, and security configuration review. Read this skill before any Entra ID operations — it enforces discovery-first patterns and strict read-only safety 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。

Use when working with Aws Lambda Deep — deep AWS Lambda analysis covering function inventory, cold start profiling, memory optimization, concurrency patterns, layer dependency auditing, dead letter queue health, event source mappings, and cost estimation. Goes beyond basic metrics to identify optimization opportunities.

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。

REQUIRED helper functions (never raw curl), project_id patterns, suggestion block syntax with offset notation

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 working with Apigee — apigee API platform management - API proxy deployment, environment configuration, analytics and traffic analysis, developer and app management. Use when managing Apigee-based API infrastructure, deploying proxies, analyzing API traffic patterns, or managing developer portal 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。

Use when working with Anthropic Api — anthropic API platform management covering models, usage tracking, rate limits, and message analytics. Use when monitoring API usage and costs, analyzing model request patterns, reviewing rate limit health, or troubleshooting Anthropic Claude API issues.

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 working with Auth0 — auth0 identity platform management for tenant configuration, application setup, connection analysis, rule and action review, user management, and log inspection. Covers universal login, social connections, enterprise federation, and Auth0 Actions pipelines. Read this skill before any Auth0 operations — it enforces discovery-first patterns and strict read-only safety 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。

MANDATORY parallel execution patterns, cluster overview script, -o json with jq filtering, batch operations, and common pitfalls

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 working with Allma — allma incident management, collaboration workflows, post-incident learning, and channel orchestration. Covers incident creation via Slack, timeline tracking, stakeholder communication, automated workflows, and retrospective analysis. Use when managing active incidents, reviewing post-incident learnings, or analyzing incident patterns in Allma.

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 working with Gcp — cost anti-hallucination rules, MANDATORY parallel execution patterns (30x speedup), monitoring aligners, reusable billing/pricing scripts, VAT/tax handling, and filtering/pagination.

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。

REQUIRED helper functions (never raw curl), workspace/repo_slug patterns, suggestion block syntax for code review

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 working with Aws — mANDATORY parallel execution patterns (30x speedup), CloudWatch statistics syntax, Cost Explorer aggregation, output token limits, and common pitfalls.

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 working with Aws S3 — aWS S3 bucket analysis, storage class distribution, lifecycle policies, access patterns, and cost optimization. Covers bucket inventory, object metrics, versioning status, encryption audit, public access analysis, and intelligent tiering evaluation.

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。

MANDATORY parallel execution patterns (30x speedup), monitor metrics aggregation, --output tsv formatting, and common pitfalls

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 working with Aws Eventbridge — aWS EventBridge event bus management, rule analysis, target health monitoring, and schema registry exploration. Covers event pattern matching, rule invocation metrics, dead-letter queue analysis, cross-account event routing, and event replay.

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 working with Aws Cloudwatch Logs — aWS CloudWatch Logs group management, Logs Insights query execution, metric filter analysis, retention policy review, and subscription filter management. Covers log group inventory, storage cost optimization, query patterns, and cross-account log 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。

Use when working with Dynamodb — amazon DynamoDB table analysis, capacity mode evaluation, GSI/LSI usage, item access patterns, and cost 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。

Eliminates AI-generated writing patterns that erode reader trust. Use when writing or editing articles, docs, or press 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。

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code.

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 after generating code, after accepting AI suggestions, or when reviewing AI-written modules. Also use when code works but feels brittle, when error handling seems thin, when orphaned resources or missing cleanup are suspected, or when the agent claims done but hidden debt may exist. Catches the specific failure patterns AI agents produce that humans would not.

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。

Query ARCHS4 REST API for uniformly processed RNA-seq expression, tissue patterns, co-expression across 1M+ human/mouse samples. Retrieve z-scores, co-expressed genes, samples by metadata, HDF5 matrices. For variant population genetics use gnomad-database; for pathway enrichment use gget-genomic-databases (Enrichr).

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。

REST API design patterns including resource naming, status codes, pagination, filtering, error responses, versioning, and rate limiting for production APIs.

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。