2.3천건 · 관련도순
Use when working with Bazel — bazel build system management. Covers BUILD file analysis, target querying, dependency graphs, remote execution, caching configuration, and build performance profiling. Use when managing Bazel workspaces, debugging build failures, querying targets, or optimizing build performance.
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Use when working with Azure Functions Deep — deep Azure Functions analysis covering function app inventory, trigger types, execution metrics, scaling behavior, slot deployments, application insights integration, and consumption plan cost tracking. Provides optimization guidance for cold starts and memory usage.
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MANDATORY parallel execution patterns, cluster overview script, -o json with jq filtering, batch operations, and common pitfalls
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Use when working with Argo Workflows — argo Workflows management for Kubernetes-native workflow orchestration. Covers workflow templates, cron workflow scheduling, artifact management, workflow execution, parameter handling, and resource monitoring. Use when checking workflow status, investigating step failures, managing templates, or auditing cron workflows.
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Use when working with Ansible — ansible automation and configuration management. Covers playbook execution, inventory management, role management, vault secrets, ad-hoc commands, fact gathering, and task debugging. Use when running playbooks, managing inventories, debugging task failures, or auditing Ansible configurations.
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Use when working with Gcp — cost anti-hallucination rules, MANDATORY parallel execution patterns (30x speedup), monitoring aligners, reusable billing/pricing scripts, VAT/tax handling, and filtering/pagination.
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MANDATORY parallel execution patterns (30x speedup), monitor metrics aggregation, --output tsv formatting, and common pitfalls
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Use when working with Azure Functions — azure Functions app analysis, execution metrics, consumption plan monitoring, scaling configuration, and deployment management via Azure CLI.
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Use when working with Gcp Cloud Functions — google Cloud Functions management, execution analysis, scaling configuration, event trigger inspection, and runtime diagnostics via gcloud CLI.
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Use when working with Aws Systems Manager — aWS Systems Manager parameter store management, session management, patch compliance tracking, and Run Command analysis. Covers parameter inventory, managed instance status, automation execution, maintenance windows, and inventory collection.
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Use when working with Aws — mANDATORY parallel execution patterns (30x speedup), CloudWatch statistics syntax, Cost Explorer aggregation, output token limits, and common pitfalls.
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Use when working with Snowflake — snowflake data warehouse analysis, query performance tuning, cost optimization, warehouse management, and schema inspection. Covers QUERY_HISTORY analysis, credit consumption, warehouse utilization, storage analysis, data sharing, and Time Travel. Read this skill before any Snowflake operations — it enforces two-phase execution, anti-hallucination rules, and read-only safety constraints.
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Use when working with Aws Cloudwatch Logs — aWS CloudWatch Logs group management, Logs Insights query execution, metric filter analysis, retention policy review, and subscription filter management. Covers log group inventory, storage cost optimization, query patterns, and cross-account log aggregation.
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PostgreSQL database analysis, performance tuning, and health monitoring. You MUST read this entire skill document before executing any PostgreSQL operations — it contains mandatory workflows, safety constraints, and two-phase execution rules that prevent common errors like hallucinated column names and unsafe queries.
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Use when working with Aws Athena — aWS Athena query execution analysis, workgroup management, Data Catalog integration, and cost-per-query tracking. Covers query history, performance optimization, workgroup quota management, saved queries, and data scanned analysis.
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Use when working with Great Expectations — great Expectations data quality framework analysis. Covers expectation suite management, validation result review, data docs generation, checkpoint execution, datasource configuration, and batch analysis. Use when reviewing data quality results, managing expectation suites, investigating validation failures, or auditing data quality configurations.
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Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.
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Delegate routine work to subagents — boilerplate generation, data transformation, file analysis, documentation drafting. Use when splitting tasks into independent subtasks for parallel subagent execution.
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Review homework notebooks for completeness, reproducibility, safe execution, and academic-integrity boundaries.
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**MANDATORY prerequisite** — you MUST invoke this skill BEFORE every `use_figma` tool call. NEVER call `use_figma` directly without loading this skill first. Skipping it causes common, hard-to-debug failures. Trigger whenever the user wants to perform a write action or a unique read action that requires JavaScript execution in the Figma file context — e.g. create/edit/delete nodes, set up variables or tokens, build components and variants, modify auto-layout or fills, bind variables to properties, or inspect file structure programmatically.
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Use taste as a competitive moat and business advantage. In the AI and vibe-coding era, execution is commoditized. Taste is the defensible edge. Use when advising founders on product differentiation, building product culture, evaluating why some products win despite fewer features, or understanding taste as a strategic asset.
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Build taste through volume of output, deliberate failure, and speed. Taste cannot be developed by watching. It's sharpened by making, failing, and making again. Use when designing practice routines, breaking through creative blocks, or helping someone move from analysis to execution.
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Use when asked to compare, cross-review, merge, judge, choose, or arbitrate competing plans from multiple agents such as Codex and Claude Code; when given two or more proposed plans, session IDs, transcripts, plan documents, PR descriptions, or pasted strategies; or when the user wants one recommended execution plan after agents review each other's proposals.
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Use for real-time performance and multimedia operator work: technical show-control execution (signal flows, OSC/DMX, MCP orchestration, hardware limits) for tools like grandMA3, Resolume, Unreal, Rhino, Vectorworks, and Adobe MCP.
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