「sic」の検索結果

Use the Classic preset for a lightweight adjustment within one change. Use when the user explicitly invokes /comet-tweak, selects tweak, or resumes workflow: tweak.

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在隔离范围内，通过所属 Native 或 Classic workflow、匹配风险的测试、生成 Runtime 检查和谨慎交付，实施已确认的 Comet GitHub Issue 或 review 阻塞项。用户明确要求修复已验证的 Issue 或 PR 问题时使用。

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。

通过 Comet Creator 创建或升级 Comet Classic workflow Skill。不用于一般 Skill 的编写、整理或评审。

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 the Classic preset to repair a localized defect. Use when the user explicitly invokes /comet-hotfix, selects hotfix, or resumes workflow: hotfix.

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。

Create or upgrade a Comet Classic workflow Skill via Comet Creator. Not for general Skill authoring, cleanup, or 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。

A playful, arcade-inspired interface for games — built on the VT323 pixel typeface, hard-edged 0px corners, chunky pill buttons that physically press into solid offset blocks

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。

Classic block-game inspired design with playful colors, bold display fonts, and compact, high-energy layouts.

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Print-inspired visual language for books, magazines, and reports with editorial grids and expressive typography.

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Apply IRQL graph functions to KQL or IRQL query results for Kusto Explorer visualization. Generates Lift_To_Graph mappings and composes Graph_Render_View, Graph_Fold_By_Property, Extract_Node_*, Enrich_Node_*, and Enrich_Graph_* calls. Accepts a supplied query or limited basic natural-language source request; it is not a general natural-language-to-KQL/IRQL skill. WHEN: Lift_To_Graph, Graph_Render_View, Graph_Fold_By_Property, IRQL graph enrichment, graph mapping for existing query results, icon-decorated graph, fold graph nodes. Use azure-kusto-graph for native make-graph analysis, graph-match, shortest paths, components, or persistent graphs.

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Cell segmentation from multiplexed tissue images. Covers deep learning (Cellpose, Mesmer) and classical approaches for nuclear and whole-cell segmentation. Use when extracting single-cell data from IMC or MIBI images after preprocessing.

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Perform differential expression analysis using DESeq2 in R/Bioconductor. Use for analyzing RNA-seq count data, creating DESeqDataSet objects, running the DESeq workflow, and extracting results with log fold change shrinkage. Use when performing DE analysis with DESeq2.

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Perform differential expression analysis using edgeR in R/Bioconductor. Use for analyzing RNA-seq count data with the quasi-likelihood F-test framework, creating DGEList objects, normalization, dispersion estimation, and statistical testing. Use when performing DE analysis with edgeR.

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Read and manipulate Flow Cytometry Standard (FCS) files. Covers loading data, accessing parameters, and basic data exploration. Use when loading and inspecting flow or mass cytometry data before preprocessing.

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Query dbSNP for rsID lookups, variant annotations, and cross-references to other databases. Use when mapping between rsIDs and genomic coordinates or retrieving basic variant information.

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。

Calculate polygenic risk scores using PRSice-2, LDpred2, or PRS-CS from GWAS summary statistics. Use when predicting disease risk from genome-wide genetic variants.

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Sets up CloudWatch observability for the first time - Omni (CloudWatch Application Observability) and classic CloudWatch. Omni: creating a Space or Domain; access grants (who has access, at what level) and access profiles bounding async alerts, integrations, or agents; instrumenting an app or AI agent with the plain ADOT SDK so traces reach Omni (Python/Node/Java/.NET on EC2/ECS/EKS/Lambda), incl. no-image-rebuild and .NET CoreCLR vars; ingesting Azure telemetry via the CloudWatch agent on an Azure VM or AKS; connecting Slack to a Space; whether GitHub or a custom MCP tool server (HTTP/stdio; API key, bearer, OAuth2) can be connected. CloudWatch: onboarding a service to Application Signals - ADOT auto-instrumentation, the amazon-cloudwatch-observability add-on, monitored service, reporting telemetry, ServiceEvents, CI/CD git/deployment metadata, Terraform/manifest edits. For using what is set up - queries, dashboards, alarms, Omni alerts, X-Ray, synthetics, Dynamic Instrumentation - use aws-observability.

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Guides building full-stack applications with AWS Blocks — an Infrastructure-from-Code framework. Applies when creating APIs, selecting Building Blocks (KVStore, DistributedTable, Database, AuthBasic, AuthCognito, Realtime, AsyncJob, FileBucket, etc.), running local development, or deploying AWS Blocks applications. Also covers AWS Blocks topics with validated, version-specific patterns that prevent common mistakes. Triggers when user mentions AWS Blocks; project has aws-blocks/ directory; code imports @aws-blocks packages.

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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.

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Run and control a user's app on a remote iOS/Android simulator hosted on EAS cloud. Read before running any `eas simulator:*` commands - it has the current syntax for this experimental API. Use whenever the user needs a simulator they can't run locally - 'run my app on a cloud simulator', 'use eas simulator to run/install/screenshot my app', 'I'm on Linux/Cursor and need an iOS device', 'no sim on this box / headless CI', 'let an agent click through my app and screenshot it', 'test my dev build on a remote sim with live reload', 'stream a sim to my browser' - even when they don't say 'EAS Simulator' or 'cloud'. On a host WITHOUT a local simulator (Linux, CI, cloud sandbox) it's the default; on macOS, do NOT auto-trigger for a plain 'run on the simulator' - use it only for a cloud/remote/shareable sim, an iOS version they lack, or an agent-driven session. NOT for local sims (expo run:ios, Xcode, Android Studio), EAS Build/Update, web preview, or physical devices.

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Analyze and apply AssemblyAI secret, region, consent, retention, deletion, and model-training controls. Use when reviewing security or regulated speech workflows. Trigger with "AssemblyAI security", "AssemblyAI privacy", or "data retention".

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Apply security best practices for Apple Notes automation scripts. Trigger: "apple notes security".

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Harden an Attio integration with least-privilege credentials, tenant isolation, log redaction, raw-body webhook verification, idempotency, and incident-ready rotation. Use when reviewing Attio security controls or preparing production access. Trigger with "Attio security", "secure Attio integration", or "Attio webhook signature".

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 Apollo.io API security best practices. Use when securing Apollo integrations, managing API keys, or implementing secure data handling. Trigger with phrases like "apollo security", "secure apollo api", "apollo api key security", "apollo data protection".

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。