Nick

Define security controls for AI coding agents used by a team. Covers command and file permissions, secret scanning, isolated execution environments, code review gates, and audit trails, with configuration examples to adapt.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Set team rules before introducing AI coding agents
• Restrict access to credentials and infrastructure files
• Design an isolated environment for agent execution

Investigate failed Agent QA runs using logs, recorded artifacts, and local source code. Make a focused code or test-definition repair, then verify the affected behavior while keeping product and infrastructure defects visible.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Repair a failed staging test from recorded evidence
• Update an outdated Agent QA YAML definition
• Distinguish test failures from product or infrastructure defects

Configure permission checks for unattended Antigravity CLI runs. The setup combines blocking rules, automatic approval for scoped operations, AI classification for ambiguous calls, and single-use approval tokens to control tool access within a verified workspace.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Setting up permission checks for unattended Antigravity CLI runs
• Defining rules for shell commands, file changes, and network access
• Configuring a local model to classify ambiguous tool calls

Design tools that AI agents can understand and call, covering input schemas, clear descriptions, validation, and error handling. The guidance includes JSON Schema, a format for defining inputs, and MCP, a protocol for connecting agent tools.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Design inputs for a new agent tool
• Improve tool descriptions that guide model choices
• Review validation and error handling

Design traffic controls for AI inference services using Istio configuration examples. Covers mutual authentication, model version routing, gradual releases, retry limits, failure containment, and monitoring, with guidance for validating changes on the target cluster.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Secure communication between inference services
• Gradually route requests to a new model version
• Review retries and failure containment for GPU services

Audit a live web page for accessibility issues and produce a fix worklist with exact element selectors, evidence, and suggested changes. Findings include impact counts and source locations when available, without editing the application.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check accessibility after a UI change
• Locate contrast and accessible-name issues
• Prepare a fix worklist with element selectors

Turns supplied AI agent evaluation results into reports that distinguish autonomous success, human-assisted success, failure, timeout, and invalid runs. Makes metric denominators, retries, timing, costs, and comparison conditions explicit to support evidence-based decisions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Separating autonomous and human-assisted success rates
• Reporting evaluations with retries and invalid runs
• Comparing agents or releases under matched conditions

Support legal questions concerning Brazilian law across family, criminal, labor, tax, consumer, real estate, business, civil, and constitutional matters. The skill directs the agent to consult an accompanying detailed guide for procedures, prerequisites, and validation requirements.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Discussing family or civil matters under Brazilian law
• Considering Brazilian labor or tax law questions
• Asking about consumer or real estate legal matters

Retrieve structured JSON from public X/Twitter post links through the third-party ADHX API. Use available text, author details, engagement counts, and long-form article content to summarize posts, extract key points, or examine audience responses.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Summarizing a public X/Twitter post from its link
• Extracting key points from an X Article
• Checking available likes, reposts, and view counts

Analyze campaign data across advertising platforms, check whether results are comparable, and assess costs and returns. Get budget test proposals with stated evidence, uncertainty, spending limits, and rollback criteria.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compare Google Ads and Meta Ads performance
• Investigate campaigns with high acquisition costs
• Plan limited tests of budget changes

Manage ActiveCampaign contacts through Rube MCP, a connection for agent tools. Find or create contacts, update tags and mailing list subscriptions, enroll contacts in existing automations, and create follow-up tasks with checks for consent and existing records.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Find or register contacts
• Organize contacts with tags
• Update mailing list subscriptions

Structure an evidence-based comparison of shortlisted accounting packages using 57 fields for capabilities, costs, and evaluator judgments. Request empty templates in CSV, SQL DDL, JSON Schema, or Notion mapping while keeping the final decision with the business.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Prepare a common comparison template for accounting packages
• Define shared tests for vendor demonstrations
• Organize quoted costs for first-year and three-year comparisons

Design a role permission matrix showing which business areas each role should view or edit, including confidentiality levels. Get a review workflow and, on request, empty CSV templates, SQL table definitions, JSON Schema, or Notion mappings.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Defining viewing and editing permissions by role
• Planning access rules for confidential records
• Preparing a quarterly access review template

Manage coding work from issue intake through implementation, review, deployment, and acceptance checks. Track each completion requirement against fresh evidence, with defined retry limits and explicit escalation when progress needs human input.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Taking a ready issue through implementation and verification
• Coordinating implementation, review, and deployment handoffs
• Checking runtime behavior against acceptance criteria

Build and debug interactive web 3D scenes with Three.js, React Three Fiber, or Spline. Plan product configurators and portfolios, prepare models, connect scroll interactions, and review loading feedback, fallback content, accessibility, and performance on target devices.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding interactive 3D product previews and variant controls
• Creating a portfolio scene linked to scrolling
• Investigating slow loading or rendering in a 3D scene

Compare accessibility findings between two versions of a web page. Identify newly introduced and fixed issues, count existing findings, and report evidence and suggested fixes without editing application code.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check accessibility before committing local changes
• Compare a page against a branch baseline
• Confirm which accessibility issues a change fixed

Turn a repeatable task into an Andru.ia skill with clear inputs, outputs, examples, and limits. Draft SKILL.md, check the folder structure and required validations, and prepare a pull request describing the changes for review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a skill for a repeatable task
• Improving an existing skill’s examples and limits
• Validating skill files and preparing a pull request

Assess a new or existing AI project by examining its code, goals, and constraints. Recommend skills confirmed to exist in the available registry, then outline tasks and implementation phases with dependencies, completion criteria, and checks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning the first steps of a new AI project
• Assessing technical issues in an existing project
• Selecting relevant skills from an available registry

Improve an existing AI agent by analyzing execution records, user feedback, and performance metrics. Refine prompts and workflows, compare original and revised versions through tests, and plan staged releases with monitoring and rollback when results worsen.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating recurring agent failures and user corrections
• Refining prompts, examples, and output formats
• Comparing original and revised agents with A/B tests

Build persistent agents on Azure AI Foundry with the Microsoft Agent Framework Python SDK. Connect functions, search, and MCP tools, preserve conversation context, stream responses, and return data in a defined structure.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building an agent that preserves conversation context
• Connecting Python functions and hosted search tools
• Displaying responses as they arrive

Compare agent, prompt, or tool configuration changes using versioned test cases and explicit outcome checks. Record each attempt, distinguish agent failures from evaluation or infrastructure problems, and report regressions, permission violations, and uncertainty.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compare agent behavior before and after prompt changes
• Reproduce an observed failure with preserved evidence
• Run regression tests after a bounded fix

Build repeatable evaluations for AI agent responses, tool choices, and multi-step tasks. Use reference datasets and scoring criteria to compare changes, detect quality regressions, and set automated checks that must pass before deployment.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compare agent quality before and after prompt changes
• Test tool selection and multi-step task execution
• Evaluate resistance to prompt injection

Compare AAS skills against a project's capabilities, then record the chosen combination as a validated stack manifest. Inspect the result, identify catalog gaps, and optionally export evidence documenting the selection process.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Prepare a project-level AAS stack for Codex
• Compare candidate skills for each project capability
• Document selected skills and catalog gaps

Check web pages and components for accessibility issues against WCAG 2.2, web accessibility guidelines. Receive a report prioritized by user impact, or request targeted code fixes followed by verification of resolved and newly introduced issues.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Get a prioritized accessibility report for a page
• Audit accessibility patterns across components
• Fix reported issues and verify the changes