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數據吞吐量加速器

當需要大量數據攝取、回填、匯出、ETL、倉庫加載、清單追趕或表格同步,且必須在保證數據正確性的前提下大幅提升速度時使用。

數據吞吐量加速器 是什麼?

這項技能旨在解決數據管線中的瓶頸問題,無論是數據移動、轉換還是儲存,目標是在確保數據正確性的同時加快數據落地速度。它首先要求區分來源提取、網路傳輸、倉庫加載、轉換、服務表新鮮度和即時尾數增長這六種不同類型的瓶頸。技能提供了一系列快速路徑啟發式方法,例如將計算移至數據所在位置、偏好倉庫原生掃描與合併、利用清單或檢查點跳過已完成的檔案、以及確保寫入操作具有冪等性。工作流程涵蓋從讀取當前合約、測量積壓量、執行安全追趕基準測試,到比較不同變體並推廣最快且保持一致性的路徑,最後將其編碼為 CLI 工具、排程任務或 Runbook。此技能適用於 Claude Code、Cursor 等開發工具中的 AI Agent,幫助開發者系統性地優化大規模數據處理性能,同時提供可稽核的會計輸出(如處理檔案數、新增行數、執行時間)來驗證正確性。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/data-throughput-accelerator

在你喜歡的 AI 中提問

開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

數據吞吐量加速器 是做什麼的?

當瓶頸在於移動、轉換或儲存大量數據時使用此技能。目標不僅是速度,而是在正確的位置以更快的速度正確落地數據,並提供可驗證的證明。

首要區分

在優化之前,請先區分以下項目:

  • 來源提取速度;
  • 網路傳輸速度;
  • 倉庫/加載速度;
  • 轉換速度;
  • 服務表新鮮度;
  • 作業運行期間的即時尾數增長。

一個管線可能「很快」,但如果新數據抵達的速度超過最終追趕視窗,它仍然可能看起來落後。

快速路徑啟發式方法

  • 將計算移至數據已經存在的地方。
  • 對於大型已落地檔案,偏好使用倉庫原生掃描、聯結和附加。
  • 使用清單或檢查點,以便跳過已完成的檔案/分割區。
  • 使用與讀取和附加模式相匹配的分割區和叢集。
  • 批次處理小檔案、請求和寫入。
  • 透過唯一鍵、清單或可替換的暫存區,使寫入操作具有冪等性。
  • 分別管理原始數據、衍生數據和服務表,以便於責任歸屬。

工作流程

  1. 讀取當前的來源、目標和清單合約。
  2. 測量積壓量:外部檔案、清單行數、原始行數、衍生行數、最小/最大時間戳記和未處理計數。
  3. 執行安全追趕或抽樣基準測試。
  4. 比較變體:批次大小、工作程序數量、倉庫 SQL、檔案分組、暫存區形狀和清單更新方法。
  5. 僅推廣在保持計數和時間戳記一致性的前提下最快的路徑。
  6. 將該路徑編碼為 CLI 工具、排程作業、工作流程或操作手冊。
  7. 在編碼後的路徑執行完畢後,重新執行最終會計核算。

會計輸出

使用嚴格的會計區塊:

數據吞吐量結果:
- 發現的來源檔案:294
- 本次運行處理的檔案:294
- 新增原始行數:9,683,598
- 新增衍生行數:8,917,585
- 回讀時的剩餘尾數:24 個檔案
- 運行時間:38.7 秒
- 正確性閘門:清單計數與表格最大時間戳記相符

護欄

  • 不要為了讓指標看起來更好看而刪除原始數據。
  • 不要默默跳過失敗的檔案。
  • 不要將歷史回填狀態與即時尾數新鮮度混為一談。
  • 在目標表與清單達成一致之前,不要宣告管線完成。
  • 對於金融、醫療保健、受監管或影響客戶的數據,請保留重播證據和核准關卡。

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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