Skillquality 0.46

jup-architect

Use when analyzing the jup codebase, identifying technical debt, suggesting architectural improvements, or ensuring high engineering standards.

Price
free
Protocol
skill
Verified
no

What it does

jup Expert Architect Assistant 🏗️

This skill helps AI agents analyze the jup codebase, identify technical debt, suggest architectural improvements, and ensure high engineering standards.

How to Use This Skill

  • Codebase Analysis: Perform deep dives into src/jup/ to understand current implementation patterns.
  • Technical Debt Audit: Identify areas where the code is fragile, complex, or difficult to test.
  • Architectural Proposals: Suggest structural changes to improve modularity, performance, or scalability.
  • Code Quality Review: Evaluate existing code against best practices for Python, Typer, and Pydantic.

Core Architectural Values

  • Modularity: Maintain clear boundaries between CLI commands (commands/), configuration (config.py), and data models (models.py). Commands should focus on CLI interaction, while logic should be extracted to utilities or models where possible.
  • Idiomatic Typer: Leverage Typer's Context for state management and shared services. Avoid global state where possible. Use verbose_state sparingly.
  • Type Safety: Use Pydantic v2 for all data models and configuration. Leverage Python 3.12+ type hints throughout.
  • Robust Error Handling: Replace print with structured logging or custom exceptions when appropriate. Ensure the CLI fails gracefully with helpful error messages and non-zero exit codes.
  • Testability: Prioritize designs that are easy to unit test. Use unittest.mock to isolate dependencies in tests.

Key Areas of Focus

  • Command Orchestration: Evaluate how commands are registered and executed. Ensure the commands/ package is easy to extend.
  • Data Persistence: Analyze how ~/.jup and the lockfile are managed. Ensure the lockfile schema is stable and migration-friendly.
  • Dependency Management: Review the use of uv and external libraries. Minimize unnecessary dependencies.
  • Testing Strategy: Suggest improvements to the current pytest suite and coverage.

Process Flow

digraph architect_flow {
    "Deep dive src/jup/" [shape=box];
    "Identify tech debt/bottlenecks" [shape=box];
    "Propose improvements" [shape=box];
    "Align with jup values?" [shape=diamond];
    "Refine proposal" [shape=box];
    "Create architectural spec" [shape=box];

    "Deep dive src/jup/" -> "Identify tech debt/bottlenecks";
    "Identify tech debt/bottlenecks" -> "Propose improvements";
    "Propose improvements" -> "Align with jup values?";
    "Align with jup values?" -> "Refine proposal" [label="no"];
    "Refine proposal" -> "Align with jup values?";
    "Align with jup values?" -> "Create architectural spec" [label="yes"];
}

Deliverables

  • Architectural Specs: Detailed specifications for structural changes in docs/superpowers/specs/.
  • Refactoring Plans: Implementation plans for cleaning up technical debt in docs/superpowers/plans/.
  • Code Quality Reports: Summaries of findings and recommendations.

Capabilities

skillsource-andraderskill-jup-architecttopic-agenttopic-agent-skillstopic-agentic-aitopic-agentstopic-ai-agentstopic-clitopic-installertopic-managertopic-skills

Install

Installnpx skills add andrader/jup
Transportskills-sh
Protocolskill

Quality

0.46/ 1.00

deterministic score 0.46 from registry signals: · indexed on github topic:agent-skills · 10 github stars · SKILL.md body (2,990 chars)

Provenance

Indexed fromgithub
Enriched2026-04-24 07:03:32Z · deterministic:skill-github:v1 · v1
First seen2026-04-23
Last seen2026-04-24

Agent access