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Nasiko 控制平面

使用實驗性的 Nasiko CLI 生命週期橋接器,進行固定版本的安裝、唯讀狀態查詢,以及需明確同意、附有遙測與祕密邊界的有條件解除安裝。

Nasiko 控制平面 是什麼?

此技能專為需要透過 ECC(ECLIPSE 指令控制器)管理 Nasiko CLI 生命週期的開發者設計。它提供一個安全、受控的橋接介面,專門處理三個核心操作:固定版本的安裝(目前為 v0.1.0)、唯讀狀態檢查,以及有擁有權驗證的解除安裝。使用此技能時,系統會強制執行嚴格的安全合約:所有安裝與解除安裝動作都必須先以 `--dry-run` 預覽、取得使用者明確同意(`--yes`),且絕不執行未經驗證的腳本或繞過規範。此外,技能明確禁止在命令參數中傳入機密資訊,並確保 Nasiko 的遙測功能為獨立選擇加入(opt-in),不會與安裝動作混為一談。此技能支援的平台取決於 ECC 環境,但其設計原則(固定版本、驗證摘要、防止腳本注入)適用於 macOS、Linux 與 Windows。開發者應注意,安裝 CLI 不代表控制平面已啟動,所有其他操作(如連線、部署)仍須直接使用 Nasiko CLI 官方指令。

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

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說明文件

Nasiko CLI 生命週期橋接器

僅在使用者明確要求 ECC 安裝、檢查或移除合格的 Nasiko CLI 時,才使用此技能。此技能不操作 Nasiko 控制平面。

安全合約

  • 以 ecc nasiko status --json 開始。狀態為唯讀。
  • 安裝永遠需要使用者明確同意並加上 --yes。
  • 僅安裝 ECC 認證的固定版本,目前為 v0.1.0。
  • 先以 ecc nasiko install --version v0.1.0 --dry-run --json 進行預覽。
  • 僅在使用者審閱過版本、註冊來源、摘要及目的地後,才執行 ecc nasiko install --version v0.1.0 --yes --json 進行安裝。
  • 僅移除仍為合格且由 ECC 管理的二進位檔,使用 ecc nasiko uninstall --version v0.1.0 --yes --json。移除前請先以 --dry-run 預覽。
  • 合格的來源為 https://github.com/Nasiko-Labs/nasiko,採用 Apache-2.0 授權;成品與解壓縮後二進位檔的 SHA-256 值均已固定。
  • 絕不要以下載的 Shell 或 PowerShell 引導腳本取代合格命令。
  • 絕不要將機密或憑證放入命令參數、記錄、技能輸出、安裝中繼資料或 ECC 狀態中。
  • Nasiko 的遙測功能以及與 Nasiko 或 Ito 的任何資料分享,必須是選擇加入(opt-in)且單獨告知。安裝不代表同意遙測。

生命週期邊界

初始的 ECC 橋接器支援合格的安裝、唯讀狀態查詢,以及附有擁有權檢查的解除安裝。請直接使用正式的 Nasiko CLI 進行連線、驗證、啟動、部署或關機等操作,直到這些動詞擁有各自經過驗證的 ECC 合約。請勿猜測 CLI 動詞。

安裝 CLI 不代表控制平面伺服器正在執行、代理人受到管理、路由或 ACL 正常運作、可觀測性完整、遙測功能已啟用,或 Ito 運算已連線。請分別回報各項狀態。

失敗行為

  • 如果平台、架構、版本、資訊清單、摘要、封存檔、二進位檔或目的地驗證失敗,請停止執行而不處理工件。
  • 請勿回退到 latest。
  • 請勿搜尋任意 PATH 目錄。請使用 ECC 的合格位置,或為開發驗證使用明確的絕對路徑 ECC_NASIKO_CLI_EXECUTABLE。
  • 請勿將部分或不完整的安裝視為成功。

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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