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Audit websites against WCAG 2.2, guidelines for making web content accessible. Combine automated checks with manual verification to identify barriers, prioritize issues by impact, and guide fixes to page structure and interactive components.

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• Audit a website for accessibility barriers
• Review keyboard access and form labels
• Fix contrast and heading structure issues

Set up Python APIs with FastAPI using organized project templates. Build routes, asynchronous database operations, authentication, and error handling, with examples for sharing dependencies and testing endpoints through a separate test database.

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• Set up a new FastAPI project
• Build a Python API with asynchronous database access
• Organize authentication and shared dependencies

Set up mutual TLS, where services verify each other's certificates, to secure internal communication. The skill guides certificate hierarchy, rotation, gradual enforcement, and troubleshooting connection failures across services and clusters.

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• Introduce zero-trust service communication
• Plan certificate rotation and expiry monitoring
• Investigate TLS handshake failures

Set communication rules for teams of AI agents. The skill explains when to use direct messages or broadcasts, how leads review plans, how teammates shut down safely, and how to troubleshoot stalled handoffs or missing communication tools.

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• Establishing communication rules for a new agent team
• Choosing direct messages or team-wide broadcasts
• Reviewing and approving a teammate's work plan

Organize complex work for a team of AI agents by splitting tasks, defining dependencies, and documenting ownership and completion criteria. Provides strategies for tracking progress, spotting blockers, and redistributing work when workloads become uneven.

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• Splitting complex work among multiple AI agents
• Mapping dependencies and execution order
• Defining file ownership and acceptance criteria

Investigate complex bugs by assigning competing explanations to parallel agents. Compare code evidence, contradictory findings, and confidence levels to identify likely root causes, then check that a fix resolves the original failure and related edge cases.

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• Investigating bugs with several plausible causes
• Tracing failures across multiple components
• Reassessing a debugging effort that has stalled

Design KPI dashboards that help teams make decisions using clearly defined performance measures. Choose relevant metrics, organize summary and detail views, document calculations, and address inconsistent figures, database load, and excessive alerts.

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• Design a SaaS executive metrics dashboard
• Build a live service health monitoring view
• Analyze retention by signup cohort

Plan systems across AWS, Azure, GCP, and OCI by comparing services and architecture patterns. Helps guide service selection, disaster recovery, migration planning, and cost decisions while considering ways to reduce dependence on a single provider.

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• Planning a system across multiple cloud providers
• Designing disaster recovery in another cloud
• Comparing cloud services for a workload

Design and review REST and GraphQL APIs with consistent naming, data structures, error responses, pagination for large result sets, and versioning strategies. Helps teams define shared standards and plan changes that existing clients can adopt gradually.

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• Designing a new REST or GraphQL API
• Reviewing API specifications before implementation
• Establishing shared API design standards

Design and review PostgreSQL database schemas by choosing suitable column types, keys, constraints, and indexes. It also guides decisions about large-table partitioning, flexible JSONB data, and schema changes on a live database without downtime.

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• Designing or reviewing a new PostgreSQL schema
• Choosing data types, constraints, and indexes
• Planning partitions for a large table

Improve slow Apache Spark jobs by reviewing data partitions, caching, memory settings, and shuffles, which move data between workers. Use the guidance to investigate bottlenecks and tune pipelines for larger datasets.

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• Investigating slow Spark jobs
• Tuning memory and executor settings
• Reducing data skew and shuffle traffic

Design dbt data transformations with clearly organized models, data quality tests, documentation, and incremental processing that updates only part of a dataset. Use it to structure analytics tables and organize a dbt project.

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• Organizing a dbt project into model layers
• Adding data quality tests
• Designing incremental updates for large tables

Build data quality checks with Great Expectations, dbt tests, and data contracts, which define shared expectations between teams. Check missing values, duplicates, and freshness, then integrate validation into data pipelines and CI/CD.

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• Check data for missing values and duplicates
• Build a dbt test suite
• Define shared data contracts between teams

Build Apache Airflow workflows for data pipelines and scheduled jobs. The skill guides task dependencies, retries, waiting for conditions, testing, and deployment, with patterns for tasks that can be safely rerun.

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• Building scheduled data pipelines
• Designing task order and dependencies
• Implementing custom tasks and condition checks

Follow Conductor's development plans using test-driven development: write a failing test, implement the change, then improve the code. Manage phase verification, progress updates, and focused git commits as tasks move toward completion.

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• Implementing tasks from plan.md
• Following the test-driven development cycle
• Verifying completion at phase checkpoints

Organize features, bug fixes, and refactors as Conductor tracks, units of related work. Create specifications and task plans, maintain status and dependency records, and preserve completed work with verification details and commit references.

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• Creating a work unit for a feature or bug fix
• Writing and reviewing specifications and task plans
• Recording task status, dependencies, and commits

Create and maintain project documents in conductor/ covering the product, technology stack, development workflow, and work units. Extract context from existing code, check document consistency before implementation, and update documentation as the project evolves.

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• Set up context documents for a new project
• Document an existing codebase for onboarding
• Check project documents before implementation