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Design and build data pipelines for ingestion, transformation, and storage. Invoke for: "data pipeline", "ETL", "data ingestion", "process this data", "batch processing", "stream processing", "data transformation", "data workflow".
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | data-pipeline |
| description | Design and build data pipelines for ingestion, transformation, and storage. Invoke for: "data pipeline", "ETL", "data ingestion", "process this data", "batch processing", "stream processing", "data transformation", "data workflow". |
| argument-hint | data source and target transformation |
| allowed-tools | Read, Write, Edit, Glob |
Category: Optimization/Research
Design reliable, observable data pipelines with proper error handling, retry logic, and data validation.
Complete Python pipeline with:
/data-pipeline build pipeline to ingest research papers from data/research/ → embeddings → data/embeddings/
Accessibility audit against WCAG 2.1 AA standards. Invoke for: "accessibility", "a11y", "WCAG", "screen reader", "aria labels", "color contrast", "keyboard navigation", "accessibility audit", "ADA compliance".
Write Architecture Decision Records (ADRs) to document significant technical decisions. Invoke for: "write ADR", "document this decision", "architecture decision record", "why did we choose X", "decision log", "record this choice", "ADR for".
Design and implement multi-agent orchestration systems. Invoke for: "multi-agent system", "orchestrate agents", "agent pipeline", "agent workflow", "how should agents communicate", "agent coordination", "task delegation to agents", "build an agent system".
AI safety review: alignment, misuse prevention, bias, fairness, and responsible AI. Invoke for: "AI safety review", "bias check", "fairness audit", "alignment", "responsible AI", "misuse prevention", "AI ethics", "safety guardrails", "could this AI system be misused".
LLM and AI agent security: prompt injection, jailbreaks, agent defense, guardrails. Invoke for: "prompt injection", "LLM security", "agent security", "jailbreak defense", "AI safety audit", "system prompt leakage", "adversarial inputs", "AI pipeline security", "tool call validation", "LLM guardrails", "model security", "is my prompt safe".
Improve algorithmic efficiency — find better algorithms and data structures. Invoke for: "algorithm improvement", "better algorithm", "O(n²) is too slow", "data structure choice", "optimize this loop", "algorithmic complexity", "time complexity".
