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    Repair GitLab CI Child Pipeline Artifact Expiry Race

    1

    Prevent GitLab child pipelines from failing when upstream artifacts expire before downstream fetch

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    Repair GitLab CI Child Pipeline Artifact Expiry Race

    Repair GitLab CI Child Pipeline Artifact Expiry Race

    Example session with this skill installed

    A compliance child pipeline starts after approval delay and cannot download a parent build manifest.

    Available sources: parent pipeline YAML, artifact expiration policy (partial excerpts only). Additional evidence requested: child trigger graph, job download error. Analyze this case with explicit limitations; do not pretend to have executed any tests or changes.

    • Read your context and instructions
    • Compiled the repair gitlab ci

    Repair GitLab CI Child Pipeline Artifact Expiry Race — EVIDENCE-LIMITED REVIEW

    Scenario received

    A compliance child pipeline starts after approval delay and cannot download a parent build manifest.

    Source register

    • S1: parent pipeline YAML — partial extract available.
    • S2: artifact expiration policy — partial extract available.
    • S3: child trigger graph — NOT PROVIDED; REQUIRED FOR VERIFICATION.
    • S4: job download error — NOT PROVIDED; REQUIRED FOR VERIFICATION.

    Concrete findings and verification

    trace artifact availability across approval wait — NEEDS VERIFICATION against supplied source excerpts and missing evidence.
    2.

    identify needs dependency and ownership — NEEDS VERIFICATION against supplied source excerpts and missing evidence.
    3. compare keep/ref policy — NEEDS VERIFICATION against supplied source excerpts and missing evidence.
    4.

    propose narrow retention and pipeline test — NEEDS VERIFICATION against supplied source excerpts and missing evidence.

    Deliverables and review gates

    • artifact dependency graph: DRAFT ONLY; do not infer unsupported outcomes.
    • expiry race proof: DRAFT ONLY; do not infer unsupported outcomes.
    • pipeline remediation tests: DRAFT ONLY; do not infer unsupported outcomes.

    Preliminary conclusion

    INCOMPLETE / REVIEW REQUIRED. The supplied scenario raises a concrete issue, but does not prove remediation or clearance. Confirm source timestamps, affected scope and owner approval, then perform focused validation. No external system was accessed or changed.

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

    About this skill

    GitLab child pipelines often fail when long approval delays cause parent artifacts to expire before the downstream jobs can fetch them. This skill provides a structured workflow to diagnose and repair these artifact expiry race conditions using evidence-based analysis. It forces a systematic check of your pipeline YAML, expiration policies, and trigger graphs to identify exactly where the timing mismatch occurs.

    What it does

    • Trace artifact availability: Maps how long artifacts remain valid against your specific approval wait times.
    • Identify dependency ownership: Analyzes needs blocks to verify downstream job requirements.
    • Compare retention policies: Audits keep and ref settings against actual pipeline execution windows.
    • Remediation testing: Generates narrow retention adjustments and pipeline tests to validate the fix.

    How it works

    1. Provide the parent pipeline YAML, artifact policies, and the specific job download error logs.
    2. The skill executes four mandatory checks to verify availability, dependencies, and policy mismatches.
    3. It generates an artifact dependency graph and evidence-based proof of the expiry race.
    4. You receive a structured verdict (SUPPORTED, BLOCKED, or UNVERIFIED) with specific remediation steps.

    Frameworks & tools

    Specifically designed for GitLab CI/CD pipelines, YAML configuration, and GitLab Runner artifact management.

    Why this beats prompting it yourself

    Generic prompts often suggest broad "expire_in: 1 week" fixes that violate security or storage policies. This skill uses a strict evidence-first approach to pinpoint the minimum necessary retention window, ensuring compliance while fixing the break.

    Use cases

    • Fix child pipelines failing after long manual approval gates.
    • Audit artifact retention for compliance-heavy CI/CD workflows.
    • Resolve intermittent missing artifact errors in complex trigger graphs.

    Known limitations

    Requires specific job logs and YAML inputs to function. It does not execute live API calls to GitLab or perform automated commits.

    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 systems, third-party accounts, or evidence not supplied. Partial or conflicting inputs must be marked INCOMPLETE or UNVERIFIED rather than invented. High-impact operational decisions require qualified owner review.

    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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    Security scan passed 24 days ago

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    Listed24 days ago
    Updated9 days ago

    What's inside

    Frequently Asked Questions

    This skill specifically resolves race conditions where manual approval delays cause parent pipeline artifacts to expire before a triggered child pipeline can access them. It provides a systematic diagnostic workflow to identify the exact timing mismatch and suggests precise retention fixes.

    You will need to provide your GitLab CI YAML configuration, your current artifact retention policies, and the specific error logs from the failed downstream jobs. The skill uses this data to map dependency windows without requiring direct access to your GitLab instance.

    No, this skill is designed for offline diagnostic analysis to maintain security; it does not require GitLab API tokens or the ability to make commits. It generates the necessary YAML adjustments and remediation steps for you to apply manually.

    Unlike generic AI prompts that might suggest insecurely long expiration dates, this skill uses an evidence-based approach to find the minimum necessary retention window. This ensures your pipelines are fixed while still adhering to your organization’s storage and compliance policies.

    You receive the full diagnostic workflow, the structured check logic for artifact availability, and a template for generating remediation reports. This includes the logic required to produce a formal 'verdict' (SUPPORTED, BLOCKED, or UNVERIFIED) for your pipeline state.

    New in DevOps & Cloud