Traverse a live Neo4j graph to identify affected modules, UCs, entities, and roles.
npx skills add https://github.com/ITSalt/NaCl --skill nacl-sa-feature
Please help me install this Agent Skill. Skill: nacl-sa-feature Source: https://github.com/ITSalt/NaCl/tree/main/nacl-sa-feature Command: npx skills add https://github.com/ITSalt/NaCl --skill nacl-sa-feature
It enables incremental feature specification by analyzing the live Neo4j graph to identify touched modules, domain entities, and use cases, enabling precise, staged work and better traceability.
Describe the feature in natural language to trigger graph-based impact analysis and selective SA updates.
High-intent search queries and answers about installing and using this skill.
Graph-based impact analysis identifies affected modules, use cases, entities, and roles by traversing a live Neo4j graph. You describe the feature in natural language to trigger the traversal, which pinpoints exactly what needs modification before any specification work begins.
Graph-driven feature spec orchestration maintains traceability by selectively invoking dependency-ordered skills to update architecture, domain models, roles, and UI. It generates a FeatureRequest artifact that ensures continuous validation scoping and phased handoff throughout the six-phase workflow.
Yes, you can use Neo4j to identify affected domain entities and use cases for incremental feature specification. The graph-first approach traverses live nodes and relationships to isolate touched modules, enabling precise staged work and comprehensive traceability.
The best way to scope validation for a feature request using a live graph is applying selective nacl-sa-* skills in dependency order. This minimizes unnecessary work by updating only the impacted architecture, domain models, roles, use cases, and UI components.
Feature spec orchestration generates a FeatureRequest artifact specifically for technical lead handoff and coordinated planning. This output encapsulates the graph-based impact analysis results and selective updates to ensure seamless phased transitions.
You need graph-first impact analysis instead of manually tracing feature dependencies when working with a complex Neo4j graph of interconnected modules, entities, and use cases. It automates identification of touched components to ensure precise staged work and strict traceability.
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