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nasiko-control-plane

Use the experimental Nasiko CLI lifecycle bridge for pinned installation, read-only status, and qualified uninstall with explicit consent and telemetry and secrets boundaries.

¿Qué es nasiko-control-plane?

nasiko-control-plane is a Claude Code agent skill that use the experimental Nasiko CLI lifecycle bridge for pinned installation, read-only status, and qualified uninstall with explicit consent and telemetry and secrets boundaries.

Compatible con~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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Documentación

Nasiko CLI Lifecycle Bridge

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.

Safety contract

  • Begin with ecc nasiko status --json. Status is read-only.
  • Installation always requires explicit user consent and --yes.
  • Install only an ECC-qualified pinned version, currently v0.1.0.
  • Preview first with ecc nasiko install --version v0.1.0 --dry-run --json.
  • Install with ecc nasiko install --version v0.1.0 --yes --json only after the user reviews the version, registry origin, digest, and destination.
  • Remove only a still-qualified ECC-managed binary with ecc nasiko uninstall --version v0.1.0 --yes --json. Preview removal with --dry-run first.
  • The qualified source is https://github.com/Nasiko-Labs/nasiko, licensed under Apache-2.0; artifact and extracted-binary SHA-256 values are pinned.
  • Never replace the qualified command with a downloaded shell or PowerShell bootstrap script.
  • Never put secrets or credentials in command arguments, logs, skill output, install metadata, or ECC state.
  • Nasiko telemetry and any sharing with Nasiko or Ito must be opt-in and separately disclosed. Installation is not telemetry consent.

Lifecycle boundary

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.

Failure behavior

  • If the platform, architecture, version, manifest, digest, archive, binary, or destination fails validation, stop without executing the artifact.
  • Do not fall back to latest.
  • Do not search arbitrary PATH entries. Use ECC's qualified location or an explicit absolute ECC_NASIKO_CLI_EXECUTABLE for development verification.
  • Do not treat a partial or ambiguous installation as success.

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

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.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

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