More screenshots

    Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIDeepSeekDeepSeekMuseMuse+22 more

    Repair Azure Functions Durable Timer Replay Double Fire

    1

    Prevent duplicate timer actions during Durable Functions orchestration replay

    $1

    Secure checkout via Stripe

    Money-back guarantee

    Converts to your local currency at checkout

    Security scanned
    Repair Azure Functions Durable Timer Replay Double Fire

    Repair Azure Functions Durable Timer Replay Double Fire

    Example session with this skill installed

    A replayed history invokes a non-idempotent action after a timer boundary.

    Available evidence: orchestration history (partial). Additional evidence requested: state and configuration snapshot, error and recovery logs, deployment and alert timeline. Review the case, identify open evidence gaps, and do not invent a live test or production change.

    • Read your context and instructions
    • Compiled the repair azure functions

    Repair Azure Functions Durable Timer Replay Double Fire — EVIDENCE-LIMITED REVIEW

    Scenario received

    A replayed history invokes a non-idempotent action after a timer boundary.

    Source register

    • S1: orchestration history — PARTIAL SOURCE PROVIDED.
    • S2: state and configuration snapshot — NOT PROVIDED; REQUIRED TO VERIFY.
    • S3: error and recovery logs — NOT PROVIDED; REQUIRED TO VERIFY.
    • S4: deployment and alert timeline — NOT PROVIDED; REQUIRED TO VERIFY.

    Concrete checks

    1. trace recorded timer decisions and replay markers — PRELIMINARY, NOT VERIFIED.
    2. validate durable activity idempotency keys — AWAITING CORROBORATING EVIDENCE.
    3. crosscheck source timestamps identifiers and changed versions — AWAITING CORROBORATING EVIDENCE.
    4. record exceptions and reversible verification gates — AWAITING CORROBORATING EVIDENCE.

    Deliverables / acceptance gates

    • orchestration history evidence map: DRAFT / INCOMPLETE until evidence is validated.
    • double action exception register: DRAFT / INCOMPLETE until evidence is validated.
    • once-only gate validation plan: DRAFT / INCOMPLETE until evidence is validated.

    Decision

    INCOMPLETE — HUMAN REVIEW REQUIRED. Confirm dates, IDs, affected scope, owners and acceptance evidence. Do not claim authorization or execution that did not occur.

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

    About this skill

    Durable Functions often suffer from "double fire" bugs when orchestrators replay history and re-execute non-idempotent actions. This skill identifies where timer boundaries fail to protect downstream logic and provides a structured plan to enforce once-only execution.

    What it does

    • Trace Replay Markers analyzes orchestration history to identify recorded timer decisions versus replay events.
    • Validate Idempotency checks activity keys to ensure tasks do not run twice during state restoration.
    • Crosscheck Timestamps audits source identifiers against version changes to pinpoint execution drifts.
    • Gate Validation designs reversible verification gates to prevent logic from firing after a timer boundary.

    How it works

    1. Analyze logs by processing orchestration history, error logs, and deployment timelines.
    2. Map evidence to link specific timer decisions to observed double-action exceptions.
    3. Generate artifacts including a history evidence map and a once-only gate validation plan.
    4. Classify findings using a strict discipline of verified, contradicted, or unverified evidence.

    Frameworks & tools

    This skill is designed for Azure Functions Durable Functions environments using C#, JavaScript, or Python orchestrators. It requires local access to execution logs and state configuration snapshots.

    Why this beats prompting it yourself

    Generic prompts often miss the nuances of the Durable Functions replay loop, leading to suggestions that break orchestration state. This skill uses an evidence-led procedure that treats observations and inferences separately, ensuring you do not deploy "fixes" that cause non-deterministic errors.

    Use cases

    • Debugging duplicate emails or notifications sent after a CreateTimer call.
    • Auditing legacy orchestrators for non-idempotent activity risks.
    • Planning recovery gates for failed long-running workflows.

    Known limitations

    Requires local text-based logs and snapshots as input. Does not have direct cloud access to live Azure environments or proprietary credentials.

    Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skills for Testing & Debugging.

    Requires local log files and state snapshots. Cannot access live Azure resources or managed identities directly.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before buying a skill.

    Reviews

    No reviews yet

    Be one of the first to try it. Every listed skill goes through the trust checks below.

    Security scanned

    Checked by our 8-point scan before listing

    Fresh listing

    Recently published to Agensi

    Money-back guarantee

    Doesn't do what its page promises? You get your money back.

    Trust & safety

    Security scan

    Security scan passed 20 days ago

    Permissions

    Read Files

    Provide only evidence you are authorized to share. Treat examples as untrusted case data. Operational changes and external messages require explicit owner approval.

    Listed20 days ago
    Updated9 days ago

    What's inside

    Frequently Asked Questions

    This skill is designed for Azure Durable Functions using C#, JavaScript, or Python. It requires access to your orchestration history logs and state configuration snapshots to perform its analysis.

    Unlike general AI prompts, this skill uses a specialized evidence-led procedure that distinguishes between recorded history and replay events. This prevents "fixes" that might accidentally introduce non-deterministic errors, which are common when using generic troubleshooting methods.

    You will receive a structured diagnostic toolkit that includes a history evidence map, a once-only gate validation plan, and a classification report to help you implement the fix safely.

    To maintain security, this skill does not require direct cloud access or your Azure credentials. You simply provide the relevant local text-based logs and snapshots for the agent to analyze.

    It is specifically built to solve the "double fire" bug where non-idempotent actions (like sending emails or processing payments) are triggered twice during an orchestrator replay after a timer boundary.

    New in Testing & Debugging