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Analyze supplied ad performance data to identify wasted spend, strong campaigns, and next tests. Compare channels, assess whether test differences are meaningful, and produce budget reallocation recommendations with a prioritized action plan.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Identify ads and keywords to pause
• Find campaigns and audiences worth scaling
• Assess whether A/B test results are meaningful

Design, refine, or review web and iOS interfaces using the product’s existing components and visual style. Consult relevant screen examples when useful, then inspect the result for layout problems, inaccessible controls, and broken interactions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing screens that fit an existing product
• Refining a dashboard or simplifying an interface
• Reviewing layouts and interactions before release

Create and manage Arize datasets for evaluation and experiments using the ax CLI. Import records from files, append examples, inspect dataset versions, and export a chosen version for offline analysis, with checks for field consistency and export completeness.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating evaluation datasets from files
• Adding examples to an existing test set
• Inspecting dataset metadata and versions

Find and evaluate a small, compatible set of AI Agent Skills for a multi-step goal. Check existing capabilities, compare candidates for fit and safety, identify overlaps, and prepare recommendations with installation subject to user approval.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choose a set of Skills for a multi-step project
• Audit installed Skills for overlap and conflicts
• Find supporting Skills for writing quality or compliance

Design Azure infrastructure from plain language or visualize existing resources as interactive diagrams. Refine the architecture through conversation, then generate Bicep infrastructure code, review it, and validate changes before deployment.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing a new Azure architecture
• Visualizing existing Azure resources
• Planning cost or security changes

Check security audit findings against code evidence and trace how untrusted input moves through a system. Guide a second review, document verification gaps, and assess draft reports against a minimum quality score before delivery.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Verifying evidence behind security review findings
• Rechecking input flows after an initial analysis
• Assessing report quality before delivery

Manage Azure DevOps projects, repositories, pull requests, pipelines, and work items through command-line tools. The skill guides authentication, resource operations, and automation scripts, with references for builds, permissions, packages, and common errors.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create and review pull requests
• Run pipelines and check builds
• Manage work items and sprints

Review AWS infrastructure code and deployed resources against the six Well-Architected pillars. Produce risk-ranked findings, remediation examples, and an architecture diagram, then create GitHub issues for tracking improvements after user confirmation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review AWS infrastructure code and deployed resources
• Prioritize findings by risk
• Prepare infrastructure code remediation examples

Create and fix Adobe Illustrator automation scripts using ExtendScript, Adobe’s JavaScript-based scripting language. Automate changes to artwork, text, layers, and artboards, process multiple files, and prepare exports such as PDF, SVG, and PNG.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Automate repeated changes to artwork and text
• Export multiple Illustrator files
• Generate artwork variations from data

Design workflows that evaluate and refine AI outputs through self-review, separate generation and evaluation roles, tests, or weighted scoring criteria. Includes patterns for structured feedback, iteration limits, and stopping when quality stops improving.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding self-review and revision loops to AI outputs
• Separating generation from evaluation
• Refining generated code using test results

Get instructions for installing and reviewing the full ai-ready skill in Copilot CLI. This wrapper explains how to add the latest version, reload skills, and request repository preparation for AI contributions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Install the full skill in Copilot CLI
• Review the skill before loading it
• Update an existing skill installation

Map an existing codebase into seven documents covering its technology, structure, architecture, conventions, integrations, tests, and concerns. Link findings to file evidence, mark unknowns, and highlight differences between stated plans and the actual implementation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Get oriented in an unfamiliar codebase
• Prepare documentation for a project handover
• Compare documented architecture with implementation

Set up telemetry, data about application operation, for web apps hosted in Azure. Choose automatic or manual instrumentation, create an Azure App Insights resource, and configure application code to send monitoring data.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add telemetry to an ASP.NET Core app hosted in Azure
• Send operational data from a Node.js app to Azure App Insights
• Configure automatic instrumentation for Azure App Service

Add Arize AX tracing to an LLM application, recording how model calls and tool executions connect. Inspect the existing code, select suitable integrations, add instrumentation, and verify that the application runs and traces reach Arize.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Setting up tracing for an LLM application
• Recording tool inputs and outputs in an agent
• Adding Arize export to an existing OpenTelemetry setup

Customize AgentRC readiness assessments to match team or organization standards. Choose or create policies that adjust check importance, disable irrelevant checks, set pass thresholds, and define requirements for automated checks in CI workflows.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Set shared readiness standards across an organization
• Focus assessments on AI tooling
• Adjust the importance of individual checks

Assess a repository’s readiness for AI agents with AgentRC and generate a standalone HTML dashboard. Review scores across nine areas, see prioritized improvements, and optionally apply scoring policies tailored to an organization.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Assessing a repository’s readiness for AI agents
• Prioritizing improvements from assessment results
• Reviewing scores under an organization’s own policy

Analyze AWS infrastructure definitions, deployed resources, usage metrics, and actual costs to identify savings opportunities. Rank recommendations by savings, risk, and effort, then create individual GitHub issues and a coordinating issue after approval.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Identify underused AWS resources
• Estimate monthly savings from configuration changes
• Prioritize cost reductions by risk and implementation effort

Plan and implement connections between Arduino devices and Azure IoT Hub, directly or through an IoT Edge gateway. Define sensor messages, device credentials, offline buffering, remote commands, and implementation tasks for firmware, gateways, and cloud services.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Connect Arduino sensors to Azure
• Design a local gateway for field devices
• Buffer sensor data during network outages

Organize human review in Arize by defining label choices, numeric ranges, or free-text feedback fields. Manage review queues and reviewers, submit annotations for individual records, and apply existing labels to project spans, or individual processing records, in bulk.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Define shared labels and scoring ranges for reviewers
• Create review queues and assign reviewers
• Record feedback on individual queue items

Edit patch release notes for GitHub Enterprise Server, correcting typos and style while preserving approved technical facts. Keep repeated notes consistent across versions and update known issue source comments so future releases inherit the same edits.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Proofread approved patch release notes
• Keep repeated notes consistent across versions
• Update source comments for known issues

Edit and validate Bazel build settings using conventions specific to CodeQL development. Follow established helpers for packaging and operating system differences, add dependencies with checksums, and check changed targets while respecting the standalone build setup.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Edit CodeQL Bazel build files
• Configure packaging for different operating systems
• Add external build dependencies

Maintain reference test data and expected results for model-routing audits, which analyze how AI models are selected. Investigate mismatches, update outputs after intentional behavior changes, and add captured workflow runs as new test cases.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating failures in model-routing reference tests
• Updating expected results after intentional analysis changes
• Adding workflow runs as new reference test cases

Guide visual changes to an existing documentation site and landing page. Apply defined limits for text width, spacing, navigation, and color so layout updates preserve readable content and a consistent visual style.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adjusting documentation page width and spacing
• Choosing where to place a new navigation link
• Updating landing page colors and typography

Turns collected repository statistics into an eight-panel PNG infographic. It shows pull request outcomes, timing, code changes, and human versus agent activity, with scripts to recalculate figures and check them against available source records.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Combining repository statistics into one image
• Updating an infographic with newer collected data
• Comparing human and agent contributions to pull requests