「replication」の検索結果

Publish, deactivate, and delete AEM content programmatically via the Cloud Service Replication API (com.day.cq.replication). Covers single-path and bulk activation, preview-tier targeting with AgentFilter, synchronous/async options, ReplicationStatus checks, permission validation, workflow process steps, and replication event handling. Use when the user needs to publish pages, activate or deactivate content, check replication status, build workflow steps that replicate content, listen to replication events, query batch publication state, or work with Replicator, ReplicationOptions, or ReplicationStatusProvider in AEM Cloud Service.

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, deactivate, and delete AEM content programmatically via the Cloud Service Replication API (com.day.cq.replication). Covers single-path and bulk activation, preview-tier targeting with AgentFilter, synchronous/async options, ReplicationStatus checks, permission validation, workflow process steps, and replication event handling. Use when the user needs to publish pages, activate or deactivate content, check replication status, build workflow steps that replicate content, listen to replication events, query batch publication state, or work with Replicator, ReplicationOptions, or ReplicationStatusProvider in AEM Cloud Service.

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。

AEM Cloud Service expert skill for replication / content distribution. Covers migration from CQ Replicator (com.day.cq.replication.Replicator) and Sling Replication Agent (org.apache.sling.replication.agent.api) to the Sling Distribution API (Distributor + SimpleDistributionRequest). Includes agent selection (publish vs preview), async response handling, author cluster coordination, service-user setup, review checklist, troubleshooting, 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。

Perform DCSync attacks by abusing MS-DRSR replication rights (DS-Replication-Get-Changes/-All) to impersonate a Domain Controller and extract KRBTGT, Domain Admin, and service account hashes for Golden Ticket forging, typically with Mimikatz. Use in authorized engagements after finding principals with replication rights, to establish long-term domain persistence, or to validate detections for replication abuse.

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。

This skill covers reproducible research pipelines and replication packages. Use when the user is setting up a research project directory structure, configuring workflow managers (Make, Snakemake, DVC), managing computational environments, preparing replication packages for journal submission, or debugging reproducibility failures. Triggers on "reproducible", "replication package", "Makefile", "Snakemake", "DVC", "pipeline", "workflow manager", "data versioning", "conda environment", "Docker", "seed management", "AEA data editor", "replication", "project structure", or "submission checklist".

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。

Assemble a submission-ready replication package to the AEA Data and Code Availability Standard (DCAS) / openICPSR / Social Science Reproduction Platform expectations — standard replication README, dataset manifest, computational-requirements capture, a Table/Figure → script:line map, and a confidential-data deposit plan. Use when user says "build the replication package", "prepare the openICPSR deposit", "make the AEA data and code package", "DCAS compliance", "assemble the deposit for the journal", or after a paper is accepted and the journal's data editor needs the package. NOT a numeric verifier — it calls /audit-reproducibility to confirm claims reproduce before packaging.

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。

End-to-end Stata replication pipeline — scaffolds numbered `.do` files in `scripts/stata/`, executes them via the `stata-mcp` MCP server, captures logs and outputs to `output/`, and produces publication-ready tables (esttab) and figures (graph export). Mirrors `/data-analysis` for R-first projects. Use when user says "stata replication", "set up Stata pipeline", "scaffold the .do files", "run Stata analysis", "AEA replication package in Stata", or when a project's analysis language is Stata not R.

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。

Single entry point for all AEM 6.5 LTS Replication skills. Covers configuring replication agents, activating/deactivating content, using the Replication API programmatically, and troubleshooting distribution issues for Adobe Experience Manager 6.5 LTS.

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。

Single entry point for all AEM 6.5 LTS Replication skills. Covers configuring replication agents, activating/deactivating content, using the Replication API programmatically, and troubleshooting distribution issues for Adobe Experience Manager 6.5 LTS.

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。

Detect DCSync attacks (MITRE T1003.006) where adversaries abuse Active Directory replication privileges to extract password hashes, by auditing Event ID 4662 for the DS-Replication-Get-Changes GUIDs and flagging non-domain-controller accounts issuing DsGetNCChanges RPC calls. Use when hunting for credential theft via Mimikatz lsadump::dcsync or Impacket secretsdump, investigating lateral movement with domain admin credentials, or auditing AD replication permissions.

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。

Validate the replication package for the sewage-house-prices project. Runs 10 checks covering script execution, file integrity, output freshness, dependency verification, data provenance, and README completeness (AEA format). This skill should be used when asked to "audit replication", "check the package", or "verify reproducibility".

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。

Prepare a replication package for the sewage-house-prices project. Generates AEA-compliant README, master script, numbered script order, install script, and deposit checklist. Validates the package against 10 verification checks. This skill should be used when asked to "prepare replication", "data deposit", "create replication package", or "package for submission".

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。

Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (randomized complete block, Latin square, incomplete block), factorial designs and interactions, and the split-plot/nested error strata hidden inside multi-batch genomics. Use when deciding the experimental unit and what counts as a replicate, planning randomization and run order, choosing a blocked/factorial/split-plot/nested layout, avoiding pseudoreplication in cell-culture or animal studies, or specifying the random-effects structure of the analysis model. For assigning samples to sequencing batches/lanes/plates and batch-effect correction see experimental-design/batch-design; for regulated clinical-trial randomization see clinical-biostatistics.

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。

Scaffolds or audits a social-science replication package and evaluates the manuscript and archived research objects against FAIR principles. Scaffold mode writes the folder structure, README, master.R, figure-table crosswalk, codebook, LICENSE placeholder, and .gitignore; audit mode grades the package against a pre-release checklist and audits data, code, materials, identifiers, licenses, access restrictions, and availability statements. Use when setting up or repairing a package, checking one before submission, auditing FAIR compliance, or drafting availability statements. Adapted from Yusaku Horiuchi’s replication-package-guide.

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。

Scaffold or audit a social-science replication package, and audit the manuscript and archived research objects against FAIR. Use when setting up or repairing a package, checking one before submission, or drafting data, code, and materials availability statements. Adapted from Yusaku Horiuchi's replication-package-guide.

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。

Hunts for Active Directory credential and replication attacks — DCSync, Golden/Silver Ticket, and DCShadow — by analyzing directory-service-access (4662), Kerberos TGS (4769), and logon (4624) events for replication abuse and forged-ticket anomalies. Activates for requests to hunt DCSync, detect golden/silver tickets, or find Active Directory replication abuse.

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。

Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (randomized complete block, Latin square, incomplete block), factorial designs and interactions, and the split-plot/nested error strata hidden inside multi-batch genomics. Use when deciding the experimental unit and what counts as a replicate, planning randomization and run order, choosing a blocked/factorial/split-plot/nested layout, avoiding pseudoreplication in cell-culture or animal studies, or specifying the random-effects structure of the analysis model. For assigning samples to sequencing batches/lanes/plates and batch-effect correction see experimental-design/batch-design; for regulated clinical-trial randomization see clinical-biostatistics.

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。

Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (randomized complete block, Latin square, incomplete block), factorial designs and interactions, and the split-plot/nested error strata hidden inside multi-batch genomics. Use when deciding the experimental unit and what counts as a replicate, planning randomization and run order, choosing a blocked/factorial/split-plot/nested layout, avoiding pseudoreplication in cell-culture or animal studies, or specifying the random-effects structure of the analysis model. For assigning samples to sequencing batches/lanes/plates and batch-effect correction see experimental-design/batch-design; for regulated clinical-trial randomization see clinical-biostatistics.

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 AEM 6.5 LTS Replication API for programmatic content activation, deactivation, and replication status management

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 AEM 6.5 LTS replication agents for content publishing, dispatcher cache flushing, and reverse replication

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。

Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (randomized complete block, Latin square, incomplete block), factorial designs and interactions, and the split-plot/nested error strata hidden inside multi-batch genomics. Use when deciding the experimental unit and what counts as a replicate, planning randomization and run order, choosing a blocked/factorial/split-plot/nested layout, avoiding pseudoreplication in cell-culture or animal studies, or specifying the random-effects structure of the analysis model. For assigning samples to sequencing batches/lanes/plates and batch-effect correction see experimental-design/batch-design; for regulated clinical-trial randomization see clinical-biostatistics.

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 AEM 6.5 LTS Replication API for programmatic content activation, deactivation, and replication status management

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 AEM 6.5 LTS replication agents for content publishing, dispatcher cache flushing, and reverse replication

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 experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so results are interpretable. Use whenever someone is planning a study, asks how to assign subjects/samples to groups, mentions randomization, blocking, stratification, controls, factorial or fractional-factorial designs, design of experiments (DOE), screening many factors, response-surface optimization, crossover or repeated-measures or split-plot designs, cluster/group randomization, Latin squares, plate layouts, batch/run-order effects, replication vs. pseudoreplication, or sequential/adaptive/group-sequential designs. Trigger even for informal phrasings like "how should I set up this experiment", "how do I avoid confounding", "what's the best way to test these 6 factors", or "assign these mice to conditions". For computing the sample size or power once the design is chosen, use statistical-power; for analyzing data already collected, use statistical-analysis.

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。