Ecosystem Integration Review for Repositories

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    Get evidence-backed findings on framework and library integrations, with exact locations and testable fixes.

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    Ecosystem Integration Review for Repositories

    Example session with this skill installed

    Review this Python repo's FastAPI/SQLAlchemy boundary. app/db.py:18 creates a session per request; lines 19-20 yield it without cleanup. No lockfile or tests are supplied.

    • Read your context and instructions
    • Compiled the ecosystem integration review

    Reviewed the supplied session-handling evidence. One lifecycle concern needs verification; no files were changed.

    Discovery and scope

    Python, FastAPI, and SQLAlchemy are identified from your description. Versions are unverified because no lockfile was supplied.

    BoundaryPriorityEvidence available
    FastAPI dependency to SQLAlchemy sessionHighReported creation and yield at app/db.py:18-20

    Finding

    LocationObserved patternImpactConfidenceRecommendation
    app/db.py:18-20A per-request session is yielded without cleanup in the described code.If nothing else closes it, database resources may remain held beyond the request.Provisional. Surrounding code and lifecycle ownership are unavailable.Find the session owner. If cleanup is absent, add exception-safe closure and test it.

    Boundary and evidence limits

    The request-to-session boundary was assessed from your description, not direct file inspection. External cleanup remains a possible explanation. No tests were supplied or executed, and version-specific behavior was not verified against official sources.

    Next steps

    • Inspect the complete dependency and registration. Acceptance: identify who owns session cleanup.
    • Add success and exception-path tests. Acceptance: verify closure after both request outcomes.
    • If cleanup is missing, propose a focused patch. Acceptance: the lifecycle tests pass without unrelated changes.

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    About this skill

    A dependency list cannot tell you whether your frameworks and libraries work together correctly. Get an evidence-based review of how your repository actually uses them, with specific findings and small, testable recommendations.

    What it does

    • Finds actual usage: Examines source code, configuration, build files, and tests rather than just installed packages.
    • Reviews integration boundaries: Follows how technologies handle requests, database access, background work, external clients, and runtime setup.
    • Supports mixed-language repositories: Identifies materially used languages without assuming the top-level project tells the whole story.
    • Explains actionable findings: Reports exact locations, likely impact, confidence, uncertainty, and a focused recommendation.
    • Checks version-sensitive claims: Consults official documentation when available and flags anything it cannot verify.

    How it works

    1. Provide repository access and ask for an integration review.
    2. Optionally name languages or technologies to prioritize and choose whether to allow web research.
    3. Receive a scoped report with findings, evidence limits, and follow-up requests you can approve separately.

    Works with

    Repositories in any language, including projects that combine languages. Reviews libraries, frameworks, runtimes, build systems, databases, messaging tools, testing tools, and SDK integrations where repository evidence supports the assessment.

    Why use this skill

    Spend less time sorting dependency lists into useful review work. Recommendations are checked against available code, configuration, tests, and official sources to reduce speculative advice.

    Use cases

    • Review database session handling in a web application.
    • Check integration assumptions before a framework migration.
    • Examine messaging boundaries across a mixed-language service.

    Known limitations

    Read-only by default. Not a broad architecture, style, security, or performance audit. Missing repository or source evidence limits conclusions.

    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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