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reverse-icenter

Automate iCenter page pulling, architecture linking, and knowledge extraction into omni-doc specs.

52|3|Updated Feb 14, 2026
Search Tags:#automation#documentation#orchestration#knowledge-extraction#parallel-execution#icenter#architecture-linking
One-click install
npx skills add https://github.com/ZTE-AICloud/Co-OmniSpec --skill reverse-icenter
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: reverse-icenter
Source: https://github.com/ZTE-AICloud/Co-OmniSpec/tree/main/skills/reverse-icenter
Command: npx skills add https://github.com/ZTE-AICloud/Co-OmniSpec --skill reverse-icenter

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, beautifulsoup4, markdownify, numpy, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill orchestrates a complete iCenter knowledge extraction workflow by pulling pages, linking them to architecture nodes, and extracting targeted knowledge artifacts (requirements, system-contexts, scenarios, logical-architectures) into the local omni-doc specs. It coordinates multiple phases and ensures outputs are cached and accessible for downstream documentation.

Core Features & Use Cases

  • Orchestrates end-to-end iCenter data pull, architecture linking, and artifact extraction.
  • Generates per-target outputs in omni-doc/specs and maintains a cache-driven execution model.
  • Supports parallel extraction tasks and progress tracking across stages.
  • Use Case: A team wants to convert a set of iCenter pages into structured docs by target (e.g., requirements, scenarios) for downstream development.

Quick Start

Trigger reverse-icenter with your iCenter root URLs and target(s) to pull pages, link architectures, and extract knowledge into omni-doc specs.

Frequently Asked Questions about reverse-icenter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate extracting iCenter pages into structured architecture documentation?▼

You can automate iCenter content processing by triggering the orchestration workflow with your root URLs and targets. It pulls pages, links architectures, and extracts knowledge artifacts like requirements and scenarios into local Omni-doc specs.

What is the best way to link iCenter requirements to logical architecture nodes?▼

Linking iCenter requirements to logical architectures is handled by pre-configured scripts that map extracted knowledge artifacts to target nodes. The process caches architecture_doc_links to ensure outputs remain accessible for downstream documentation.

Does this iCenter knowledge extraction tool support parallel execution for multiple targets?▼

Yes, iCenter knowledge extraction supports parallel execution across multiple targets. It coordinates extraction phases for requirements, system-contexts, scenarios, and logical-architectures while tracking progress across all stages.

Do I need local Python dependencies and network access to pull iCenter data?▼

Yes, pulling iCenter data requires local Python dependencies including requests, beautifulsoup4, markdownify, and numpy. Network access to iCenter services is also required to retrieve pages and execute the orchestration workflow.

Where are the extracted iCenter knowledge artifacts stored locally?▼

Extracted iCenter knowledge artifacts are written locally under omni-doc/specs/{target}. The workflow generates per-target outputs for requirements, system-contexts, scenarios, and logical-architectures using a cache-driven execution model.

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