Repository Architecture Review: Ownership & Boundaries

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    Get architecture findings and a phased refactor plan that clarify ownership and reduce the scope of future changes.

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    Repository Architecture Review: Ownership & Boundaries

    Example session with this skill installed

    Review our architecture: orders/service.py parses PostgreSQL constraint names; api/orders.py maps its errors to HTTP. Propose a small refactor, without editing code.

    • Read your context and instructions
    • Compiled the repository architecture review

    Assessed the boundary you described. This is a provisional review based on your summary, not a repository inspection. No code was changed.

    Architecture Review

    Ownership Map

    • orders/service.py: applies order rules, but also interprets database-specific failures.
    • api/orders.py: converts application errors into HTTP responses.
    • Persistence owner: not identified in the supplied context.

    Finding

    PriorityLocationIssueArchitectural reasonSmallest useful actionRisk if unchanged
    P2, provisionalorders/service.pyParses PostgreSQL constraint namesBusiness behavior depends on database namingMove interpretation to the existing persistence boundaryA constraint rename may require service changes

    The HTTP mapping is not itself a concern. Confirm whether the service intentionally owns persistence before treating this as misplaced responsibility.

    Refactor Plan

    1. Locate the database access owner and document which failures represent expected conflicts. Scope: order persistence and its direct caller.
    2. Translate those failures there, then let the service handle meaningful outcomes. Keep unexpected failures distinct and HTTP behavior unchanged.

    Validate conflict and unexpected-failure paths. Roll back the translation and caller changes together if behavior differs.

    Next steps

    • Inspect both files and the database access code.
    • Confirm ownership, then approve the targeted change.

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    About this skill

    When one feature change touches unrelated modules, it is hard to know where the real problem lives. Get an evidence-backed architecture review showing unclear ownership, conflicting rules, and targeted improvements instead of a broad rewrite.

    What it does

    • Maps responsibilities: Explains what major modules own and where important rules belong.
    • Finds structural risks: Identifies duplicated concepts, scattered policies, unclear boundaries, and departures from documented decisions.
    • Explains change impact: Shows why a single concept change may require edits across several modules.
    • Prioritizes improvements: Delivers findings with concrete locations and a phased refactor plan.
    • Accounts for context: Distinguishes new problems from documented compromises and flags uncertainty when evidence is incomplete.

    How it works

    1. Point the assistant at a local repository and describe the architecture question.
    2. Ask for a repository-wide review or focus on a specific concept or boundary.
    3. Receive an architecture map, prioritized findings, and recommended next steps.
    4. Decide which changes to approve. Review alone does not modify code.

    Works with

    Local code repositories, architecture documents, configuration files, and decision records. The review is general-purpose rather than tied to a particular language or framework.

    Why use this skill

    It helps developers and technical leads choose smaller refactors with clearer ownership. Location-based findings make recommendations easier to discuss and turn into scoped work.

    Use cases

    • Assess ownership before adding a new workflow.
    • Investigate business rules duplicated across services.
    • Compare implementation with architecture decisions.
    • Plan incremental cleanup of tangled module boundaries.

    Known limitations

    Requires repository access for evidence-backed findings. It does not replace bug-focused code review, testing review, or performance analysis.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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