Check whether Nasiko CLI is installed, preview installation of a fixed, verified version, and remove an ECC-managed installation. The workflow uses ECC commands, requires consent for installation, and checks ownership before removal.
中文简介正在准备中。当前显示英语简介。
Manage the experimental Nasiko CLI lifecycle through ECC — read-only status checks, consent-gated install of the pinned qualified version with dry-run preview, and ownership-checked uninstall, under explicit telemetry and secrets boundaries. Use when the user asks to install, inspect, or remove the Nasiko CLI or check whether it is present.
安装前可以查看交给 AI 代理的指令内容。
Use this skill when a user explicitly asks ECC to install, inspect, or remove the qualified Nasiko CLI. This skill does not operate a Nasiko control plane.
ecc nasiko status --json. Status is read-only.--yes.v0.1.0.ecc nasiko install --version v0.1.0 --dry-run --json.ecc nasiko install --version v0.1.0 --yes --json only after the
user reviews the version, registry origin, digest, and destination.ecc nasiko uninstall --version v0.1.0 --yes --json. Preview removal with
--dry-run first.https://github.com/Nasiko-Labs/nasiko, licensed
under Apache-2.0; artifact and extracted-binary SHA-256 values are pinned.The initial ECC bridge supports qualified installation, read-only status, and ownership-checked uninstall. Use the canonical Nasiko CLI directly for connection, authentication, launch, deployment, or shutdown until those verbs have their own verified ECC contracts. Do not guess CLI verbs.
Installing the CLI does not prove that a control-plane server is running, an agent is governed, routing or ACLs work, observability is complete, telemetry was enabled, or Ito compute is connected. Report each state separately.
latest.PATH entries. Use ECC's qualified location or an
explicit absolute ECC_NASIKO_CLI_EXECUTABLE for development verification.还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问，或说明在哪些环境下无法运行。
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Design and audit interfaces for Web, iOS, and Android using WCAG 2.2 accessibility guidance. Check screen-reader labels, keyboard navigation, contrast, and control sizes to identify barriers and guide implementation for people using assistive technology.
中文简介正在准备中。当前显示英语简介。
Investigate unreliable AI agents across 12 layers, including instructions, memory, tool execution, and display. Use code and logs to trace failures, rank findings by severity, and produce an ordered repair plan that prioritizes code changes.
中文简介正在准备中。当前显示英语简介。
Compare coding agents on tasks from your own codebase. Define success checks, run agents in separate Git working directories, and report pass rates, available API costs, completion time, and consistency across repeated trials.
中文简介正在准备中。当前显示英语简介。
Design and refine an AI agent’s available actions, tool inputs, and result formats. Define recovery steps for errors, manage the information kept in context, and evaluate changes through completion rates, retries, and cost per successful task.
中文简介正在准备中。当前显示英语简介。
Diagnose failed AI agent runs by capturing errors, checking likely causes, and choosing small, reversible recovery actions. The workflow produces a structured report of the failure, recovery steps, and evidence, helping explain repeated retries or stalled progress.
中文简介正在准备中。当前显示英语简介。
Diagnose AI agent runs that fail repeatedly, loop through tools, or lose track of the task. Capture errors and environment details, test a focused recovery action, and produce a report explaining the evidence and outcome.
中文简介正在准备中。当前显示英语简介。