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    Code Health Auditor

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    Find material code and architecture risks, separate evidence from opinion, and plan safer, higher-impact remediation.

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    Code Health Auditor

    Code Health Auditor

    Example session with this skill installed

    Audit this small service using only the supplied fictional evidence. It has 42 modules; OrderService is 1,200 lines and handles API parsing, database queries, retries, and email notifications. Three controllers duplicate authorization checks. Unit coverage is 28%, but no test results are included. A recent deployment had two timeouts; logs show repeated database retries but no trace IDs. Please separate observed facts from hypotheses, prioritize issues by risk and confidence, and give a safe 30-day remediation plan. Do not claim you inspected source files or ran tests.

    • Read your context and instructions
    • Compiled the code health auditor

    Code health assessment

    Scope: This review uses only the fictional facts in the prompt. No repository, source code, test suite, or runtime telemetry was inspected. The findings below are signals to verify, not confirmed defects.

    Executive summary

    The strongest near-term concerns are duplicated authorization logic, mixed responsibilities in OrderService, and a timeout/retry pattern that may amplify database load. Limited unit coverage and missing trace IDs reduce confidence during changes and incident investigation. Start with evidence collection and small changes that preserve behavior.

    Findings

    PriorityEvidence providedAssessmentConfidenceValidation
    HighThree controllers duplicate authorization checksPolicy drift or inconsistent enforcement is possible; duplication alone does not prove a bypassMediumCompare checks and tests across routes; confirm centralized policy expectations
    HighRecent timeouts and repeated database retriesRetry amplification or slow queries may contribute; causality is unverifiedLow–mediumCorrelate timestamps, request IDs, DB metrics, query latency, and retry policy
    MediumOrderService is 1,200 lines and handles parsing, queries, retries, emailHigh change coupling and difficult testing are plausibleMediumMap responsibilities, change hotspots, dependencies, and side effects
    MediumUnit coverage reported at 28%Coverage is low by the supplied measure, but coverage percentage alone does not indicate test qualityHigh for reported value; low for impactIdentify critical paths and assertion quality; inspect test gaps
    MediumLogs lack trace IDsCross-component request diagnosis may be difficultHigh if prompt is accurateCheck logging context propagation and available correlation fields

    30-day remediation roadmap

    Days 1–5: Establish evidence. Confirm route inventory, authorization policy, timeout rates, database saturation, retry counts, and affected customer journeys. Add temporary correlation IDs if approved. Capture a baseline for errors, latency, and query load.

    Days 6–12: Contain operational risk. Review retry limits, exponential backoff, jitter, timeouts, and idempotency with service owners. Add tests for expected retry behavior. Do not simply disable retries or raise timeouts without understanding downstream impact.

    Days 13–20: Reduce policy drift. Compare the three controller checks against a shared authorization policy. Add regression tests for allowed and denied cases, including tenant boundaries. Centralize only after behavior is understood and reviewed by the security owner.

    Days 21–30: Improve changeability. Select one cohesive OrderService responsibility, such as notification delivery, and define a seam with explicit inputs and side effects. Refactor behind behavior-preserving tests. Expand tests around critical order flows rather than chasing a coverage target alone.

    Guardrails

    • Require reviewer ownership for authorization changes.
    • Keep changes small, feature-flagged where practical, and reversible.
    • Compare baseline latency, error rates, and database load after rollout.
    • Do not label a concern a vulnerability or root cause until reproduced or independently verified.

    Next steps

    Request representative source excerpts, route/test inventory, relevant sanitized logs and traces, and architecture intent. Confirm product criticality and recent change history. Re-rank findings after evidence review, then assign owners and validation criteria.

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    About this skill

    Code Health Auditor

    Assess codebases and engineering artifacts for technical debt and architectural problems that materially affect defect risk, security, reliability, performance, change cost, delivery speed, or scale. Review modules, dependencies, data access, interfaces, errors, concurrency, configuration, tests, observability, build/deploy practices, and architecture fit against the stated intent and product criticality.

    The audit separates verified defects, probable defects, architecture concerns, maintainability debt, security and reliability risks, performance hypotheses, testability gaps, documentation issues, intentional tradeoffs, style preferences, and unknowns. Findings include evidence, affected scope, impact, confidence, priority, remediation options, dependencies, and validation steps. The result is a risk-ranked report and pragmatic remediation roadmap with quick wins, sequencing, owners, and prevention measures.

    This skill does not claim to execute builds or tests, inspect files, access repositories, or verify runtime behavior unless that evidence or access is explicitly provided. It does not present taste as fact or infer security incidents from style issues. Confirm findings with maintainers and validate changes through appropriate tests and production safeguards.

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