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logging-metrics-tracing-standard
Observability standards for services: structured logging schema, metrics naming and label rules, trace context propagation, correlation IDs, sensitive-data handling, and cardinality controls
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探索开发、内容、数据与办公效率等 AI 技能。先比较用途和仓库热度，再查看技能说明与来源。
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docs-indexing-strategy
How to organize and index documentation for humans and AI: taxonomy, metadata, cross-linking, freshness reviews, and automated index generation
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developer-onboarding-documentation
Comprehensive onboarding documentation to get new developers productive quickly with clear guides, checklists, and resources.
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database-transactions
Comprehensive guide to database transactions, ACID properties, isolation levels, locking, and distributed transactions.
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incident-triage
Rapid assessment and initial response processes for production incidents
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data-quality-monitoring
Techniques and tools for ensuring the accuracy, completeness, and reliability of data across the pipeline.
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human-in-the-loop-workflows
Implementing human approval and review workflows for AI systems to ensure quality, safety, and compliance.
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multi-cloud-patterns
Architecture patterns and strategies for multi-cloud deployments to avoid vendor lock-in.
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dependency-mapping
Comprehensive guide to identifying, visualizing, and managing dependencies in complex projects to reduce risks and enable coordination
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saga-pattern
Implementing distributed transactions across microservices using the Saga pattern with choreography and orchestration approaches.
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connection-pooling
Implementing and optimizing database connection pools for high-performance applications.
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environment-matrix-devstgprod
Environment standards for development, staging, and production: parity principles, data and access policies, configuration boundaries, and deployment controls
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tenant-aware-ops
Operational patterns for multi-tenant systems: tenant-safe debugging and monitoring, per-tenant maintenance and migrations, fairness controls, and compliance-aware access
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llm-judge-patterns
Comprehensive guide to using LLMs as judges for automated evaluation including prompt patterns, calibration, bias reduction, and multi-judge ensembles
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architecture-review
Structured process for reviewing and validating architectural decisions before implementation to catch issues early.
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schema-management
Strategies for managing data structures, versioning, and evolutions across databases and event streams.
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repo-map-ssot
Single source of truth for repository structure and entry points, including key directories, domain boundaries, shared code, integrations, and build/deploy references
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lineage-and-provenance
See the main Data Lineage skill for comprehensive coverage of data lineage tracking and provenance.
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db-migration-generator
Generator สำหรับสร้าง database migration files พร้อม up/down scripts, validation และ rollback safety
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ground-truth-management
Comprehensive guide to creating, managing, and maintaining ground truth datasets for AI evaluation including annotation, quality control, and versioning
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bulkhead-patterns
Resource isolation strategies to prevent cascading failures and limit blast radius in distributed systems
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event-sourcing
Implementing event sourcing pattern for maintaining application state as a sequence of immutable events.
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data-quality-checks-and-validation
Implementing comprehensive data quality checks across the data pipeline to ensure accuracy, completeness, and reliability.
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retry-timeout-backoff-strategies
Comprehensive guide to implementing robust retry logic, timeout handling, and backoff algorithms for resilient distributed systems
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默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。