How does it handle architectural decision-making?

It enforces a pattern of proposing multiple options with explicit tradeoffs and 'what could go wrong' scenarios, ensuring decisions are well-vetted and documented as 'nuggets' in a knowledge graph.

What are 'nuggets' in this context?

Nuggets are units of information stored in the knowledge graph. This skill distinguishes between 'state' nuggets (current code details) and 'decision' nuggets (the reasoning and constraints behind the code).

How does the skill prevent 'forensic spirals'?

It limits investigation depth to a maximum of 10 tool calls before requiring a summary and specific questioning, preventing the AI from wandering too deep into the codebase without progress.

What is the primary purpose of the Orca Architecture skill?

It is designed to provide guidance and structured workflows for discussing, exploring, and documenting the architecture of Orca-based projects using knowledge graphs.

Orca Architecture Architect

Name: Orca Architecture Architect
Author: dkoosis

bydkoosis

開発者ツール

Facilitates structured architecture discussions and knowledge-graph-driven decision capture for Orca-based systems.

概要

The Orca Architecture skill provides a disciplined framework for managing the evolution of complex software systems, specifically optimized for the Orca ecosystem. It leverages a knowledge graph to track architectural decisions, constraints, and system state, ensuring that the 'why' behind code is never lost. By enforcing bounded exploration patterns and multi-option proposal workflows, it prevents developers from falling into forensic spirals and helps maintain a source of truth for architectural reasoning through the use of 'nuggets.'

主な機能

Bounded exploration patterns to prevent investigative rabbit holes
Specialized search tools for retrieving architectural history and constraints
Knowledge Graph integration for context-aware architecture retrieval
0 GitHub stars
Multi-option proposal generation with explicit trade-off analysis
Structured decision capture workflows that prioritize reasoning over state

ユースケース

Validating proposed changes against existing system constraints and telemetry design
Planning and documenting major refactors of Orca system components
Onboarding to complex codebases by querying architectural decision history

概要

主な機能

Bounded exploration patterns to prevent investigative rabbit holes
Specialized search tools for retrieving architectural history and constraints
Knowledge Graph integration for context-aware architecture retrieval
0 GitHub stars
Multi-option proposal generation with explicit trade-off analysis
Structured decision capture workflows that prioritize reasoning over state

ユースケース

Validating proposed changes against existing system constraints and telemetry design
Planning and documenting major refactors of Orca system components
Onboarding to complex codebases by querying architectural decision history