tenacity retry gap scanner

    1

    Finds unprotected outbound Python calls and generates production-ready Tenacity retry snippets.

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    tenacity retry gap scanner

    Example session with this skill installed

    Scan ./services/payments for missing retries and generate fixes.

    • Read your context and instructions
    • Compiled the tenacity retry gap
    • Generated the document

    I have completed the resilience audit of the ./services/payments directory. I scanned 14 Python files and identified 3 high-risk gaps where outbound calls lack transient failure protection.

    Tenacity Retry Gap Report

    IDSeverityLocationIssue
    GAP-1-a8f2Highservices/payments/client.py:42Unprotected httpx.post call to Stripe API
    GAP-3-b9c1Mediumservices/payments/db.py:88sqlalchemy commit without deadlock retry
    GAP-2-e4d5Highservices/payments/notifier.py:15boto3.client('sns').publish missing retry config

    Recommended Fix: GAP-1-a8f2 (Stripe API)

    The following snippet has been generated in ./output/patches/GAP-1-a8f2.py. It uses tenacity to handle transient network errors and 429/5xx status codes specifically for the httpx library.

    import logging
    import httpx
    from tenacity import (retry, retry_if_exception, stop_after_attempt, 
                          stop_after_delay, wait_exponential_jitter, before_sleep_log)
    
    log = logging.getLogger(__name__)
    _TRANSIENT_STATUS = {408, 429, 500, 502, 503, 504}
    
    def _is_transient(exc: BaseException) -> bool:
        if isinstance(exc, (httpx.TimeoutException, httpx.NetworkError)):
            return True
        return isinstance(exc, httpx.HTTPStatusError) and exc.response.status_code in _TRANSIENT_STATUS
    
    @retry(
        retry=retry_if_exception(_is_transient),
        stop=stop_after_attempt(3) | stop_after_delay(15),
        wait=wait_exponential_jitter(initial=1, max=10),
        before_sleep=before_sleep_log(log, logging.WARNING),
        reraise=True,
    )
    def post_transaction(client: httpx.Client, payload: dict):
        # Wrapped to handle transient Stripe connection issues
        resp = client.post("https://api.stripe.com/v1/charges", json=payload)
        resp.raise_for_status()
        return resp.json()
    

    Next steps

    1. Review the full report at ./output/tenacity-retry-gap-scanner-report.md.
    2. Apply the generated patches in ./output/patches/ to your source files.
    3. Ensure tenacity is added to your requirements.txt or pyproject.toml.

    tenacity-retry-gap-scanner.pdf

    PDF · document

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Audit Python code for missing transient error handling.Generate library-specific @retry decorators for HTTP and Cloud SDKs.Prioritize network hardening based on call severity and blast radius.Calculate retry coverage metrics across a microservice.

    About this skill

    The problem

    Network calls to external APIs, databases, and cloud SDKs often fail due to transient issues. Without proper retry logic, these blips lead to avoidable production incidents, data inconsistency, and degraded user experiences.

    What it does

    • Identifies unprotected outbound calls in Python code, including requests, httpx, boto3, and psycopg.
    • Calculates a retry coverage ratio to benchmark your application's resilience.
    • Generates syntax-checked tenacity @retry snippets tailored to specific library exception hierarchies.
    • Ranks findings by severity, prioritizing user-facing request paths and high-blast-radius calls.
    • Detects existing library-level retry configurations to prevent redundant nested retry layers.

    Frameworks & tools

    Python, Tenacity, HTTPX, Requests, Aiohttp, Boto3, SQLAlchemy, Redis, Pika, and Stripe SDK.

    Why this beats prompting it yourself

    Manual audits are prone to missing deeply nested SDK calls or subtle library-level configurations already in place. This skill enforces a consistent, production-ready retry pattern with exponential backoff and jitter, preventing the common mistake of wrapping non-idempotent operations or permanent 4xx errors.

    Use cases

    • Hardening a microservice before a high-traffic launch.
    • Auditing a legacy codebase for transient failure points.
    • Standardizing resilience patterns across a distributed team.
    • Reducing Sentry/Datadog noise caused by flaky third-party APIs.

    Known limitations

    Only analyzes Python codebases. Cannot resolve client types for dynamically injected attributes, which may result in lower confidence findings.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

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    Verified clean 14 days ago

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