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    Repair Argo CD Sync Wave Hook Race

    1

    Fix pre-sync hook execution that races a later Argo CD sync wave

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    Repair Argo CD Sync Wave Hook Race

    Repair Argo CD Sync Wave Hook Race

    Example session with this skill installed

    Two app-of-apps syncs start overlapping hooks with incompatible readiness gates.

    Available evidence: sync wave event log (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 argo cd

    Repair Argo CD Sync Wave Hook Race — EVIDENCE-LIMITED REVIEW

    Scenario received

    Two app-of-apps syncs start overlapping hooks with incompatible readiness gates.

    Source register

    • S1: sync wave event log — 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. compare sync-wave annotations and hook delete policies — PRELIMINARY, NOT VERIFIED.
    2. verify ready-gate timing and rollback sequence — 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

    • sync wave event log evidence map: DRAFT / INCOMPLETE until evidence is validated.
    • hook race exception register: DRAFT / INCOMPLETE until evidence is validated.
    • ordered sync 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

    Race conditions between pre-sync hooks and downstream sync waves can break complex Argo CD deployments, especially in app-of-apps patterns. This skill provides an evidence-led method to identify and fix these overlaps by auditing annotations, delete policies, and readiness gates. It moves beyond guesswork by enforcing a strict classification system for logs and configuration snapshots.

    What it does

    • Race Condition Auditing by comparing sync-wave annotations against hook delete policies to find execution overlaps.
    • Timing Verification of readiness gates and rollback sequences to identify why hooks are firing before dependencies are settled.
    • Evidence Mapping that links sync-wave event logs to specific timestamps and resource identifiers.
    • Exception Registration to document every hook race and its impact on the deployment timeline.
    • Validation Planning to generate an ordered sequence of changes required to resolve the race.

    How it works

    1. Analyze Sources using sync-wave event logs, state snapshots, and deployment timelines provided in the context.
    2. Crosscheck Identifiers to align source timestamps with changed resource versions across overlapping syncs.
    3. Classify Evidence by marking every observation as VERIFIED, CONTRADICTED, or UNVERIFIED based strictly on the provided data.
    4. Draft Validation Plan including reversible verification gates and explicit owner approval steps before any file modifications.

    Frameworks & tools

    This skill is designed for Argo CD environments utilizing the app-of-apps pattern, Kubernetes manifests, and Helm charts.

    Why this beats prompting it yourself

    Standard prompts often hallucinate timing data or suggest generic "sleep" fixes. This skill enforces a decision discipline that separates observations from inferences, ensuring you only act on verified log evidence.

    Use cases

    • Debugging app-of-apps syncs where hooks are executing out of order.
    • Resolving hook delete policies that trigger before readiness gates are satisfied.
    • Audit trailing logs after a failed deployment to map exact race condition timestamps.

    Known limitations

    Does not have direct cloud access. Requires local text files for sync logs, configuration snapshots, and event timelines to be provided.

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

    Cannot verify inaccessible environments or data not supplied. Missing or contradictory evidence must be marked INCOMPLETE or UNVERIFIED. Owner approval is required for operational or compliance decisions.

    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.

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    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 specifically targets race conditions where pre-sync hooks fire prematurely or overlap with downstream sync waves, a common failure point in complex app-of-apps patterns that standard linting tools miss.

    No direct cluster access is needed; the skill operates by analyzing text-based sync logs, event timelines, and manifest snapshots provided within the AI agent's context window.

    The skill outputs a structured 'Validation Plan' that includes the specific annotation adjustments, delete policy changes, and readiness gate sequences required to resolve the identified race condition.

    Yes, the skill is framework-agnostic and works with both raw Kubernetes manifests and Helm-generated charts, provided you can provide the rendered output or source templates.

    You receive the production-ready AI agent skill, a guide on extracting the necessary evidence logs from Argo CD, and a template for documenting race condition exceptions.

    The skill is compatible with any AI agent platform that supports custom instructions and long-context window file analysis, such as ChatGPT, Claude, or specialized DevOps AI workbenches.

    New in DevOps & Cloud