osdu

What this skill does

<osdu-command>
  <objective>
    Analyze GitLab CI/CD test job reliability for OSDU platform projects, tracking test job pass/fail status across pipeline runs to identify flaky tests and provide quality metrics.
  </objective>

  <triggers>
    <use-when>
      <trigger>OSDU project test status queries ("how is {project} looking", "partition test quality")</trigger>
      <trigger>Flaky test detection ("are there flaky tests in {project}")</trigger>
      <trigger>Pipeline health monitoring ("recent pipeline failures")</trigger>
      <trigger>Cloud provider comparison ("azure vs aws test reliability")</trigger>
      <trigger>Stage-specific analysis ("unit test status", "integration test failures")</trigger>
    </use-when>

    <skip-when>
      <condition>Individual test case tracking (we track job-level, not test-level)</condition>
      <condition>Non-test jobs (build, deploy, lint, security scans)</condition>
      <condition>Non-OSDU projects or non-GitLab CI systems</condition>
      <condition>Real-time monitoring (data is from completed pipelines only)</condition>
    </skip-when>
  </triggers>

  <tracking-scope>
    <hierarchy>
      Pipeline Run → Test Stage (unit/integration/acceptance) → Test Job → Test Suite (many tests)
    </hierarchy>

    <capabilities>
      <supported>Test job pass/fail status across multiple pipeline runs</supported>
      <supported>Flaky test job detection (jobs that intermittently fail)</supported>
      <supported>Stage-level metrics (unit/integration/acceptance)</supported>
      <supported>Cloud provider breakdown (azure, aws, gcp, ibm, cimpl)</supported>
      <unsupported>Individual test results (not tracked)</unsupported>
      <unsupported>Non-test jobs like build, deploy, lint</unsupported>
    </capabilities>

    <example>
      Pipeline #1: job "unit-tests-azure" → PASS (100/100 tests passed)
      Pipeline #2: job "unit-tests-azure" → FAIL (99/100 tests passed)
      Pipeline #3: job "unit-tests-azure" → PASS (100/100 tests passed)
      Result: This job is FLAKY (unreliable across runs)
    </example>
  </tracking-scope>

  <query-strategy importance="critical">
    <token-usage-reference>
      <query type="status.py --format json" pipelines="5" projects="1" tokens="900" speed="10s" safety="always-safe"/>
      <query type="analyze.py --format json" pipelines="5" projects="1" tokens="35000" speed="30s" safety="use-cautiously"/>
      <query type="analyze.py --format json" pipelines="10" projects="1" tokens="68000" speed="60s" safety="heavy"/>
      <query type="analyze.py" pipelines="10+" projects="multiple" tokens="100000+" speed="120s+" safety="avoid"/>
      <query type="analyze.py" pipelines="all" projects="30" tokens="200000+" speed="180s+" safety="exceeds-limit"/>
    </token-usage-reference>

    <progressive-approach mandatory="true">
      <step number="1" name="start-light">
        <action>Use status.py for quick overview</action>
        <command>script_run osdu status.py --format json --pipelines 3 --project {name}</command>
        <rationale>Lightweight, fast, safe token usage</rationale>
      </step>

      <step number="2" name="deep-dive" condition="only-if-needed">
        <action>Use analyze.py with strict filters</action>
        <command>script_run osdu analyze.py --format json --pipelines 5 --project {name} --stage unit</command>
        <rationale>Heavy query, use only when status insufficient</rationale>
      </step>

      <step number="3" name="never-query-all">
        <action>ALWAYS specify --project to avoid 30-project scan</action>
        <rationale>Prevents token limit exceeded error</rationale>
      </step>
    </progressive-approach>

    <format-selection>
      <format type="json">
        <use-when>Extracting specific metrics or calculating statistics</use-when>
        <use-when>Building summaries or comparisons</use-when>
        <use-when>Parsing structured data programmatically</use-when>
        <use-when importance="critical">ALWAYS for status.py (lightweight, parseable)</use-when>
      </format>

      <format type="markdown">
        <use-when>Analyze.py queries (10x smaller than JSON, still readable)</use-when>
        <use-when>Creating reports for sharing</use-when>
        <use-when>Need human-readable tables without parsing</use-when>
        <use-when>Token budget is tight</use-when>
      </format>

      <format type="terminal" status="never-use">
        <avoid-because>Includes ANSI codes and colors, hard to parse</avoid-because>
        <avoid-because>Only for direct human terminal viewing</avoid-because>
      </format>
    </format-selection>
  </query-strategy>

  <available-projects count="30">
    <core-services description="Most Common Queries">
      <project name="partition" description="Multi-tenant data partitioning"/>
      <project name="storage" description="Blob/file storage service"/>
      <project name="indexer-service" description="Search indexing"/>
      <project name="search-service" description="Search API"/>
      <project name="entitlements" description="Auth/permissions"/>
      <project name="legal" description="Legal tags/compliance"/>
      <project name="schema-service" description="Schema registry"/>
      <project name="file" description="File metadata management"/>
    </core-services>

    <domain-services>
      <project name="wellbore-domain-services" description="Wellbore data"/>
      <project name="well-delivery" description="Well delivery workflows"/>
      <project name="seismic-store-service" description="Seismic data storage"/>
      <project name="dataset" description="Dataset management"/>
      <project name="register" description="Data registration"/>
      <project name="unit-service" description="Unit conversion"/>
    </domain-services>

    <reference-services>
      <project name="crs-catalog-service" description="Coordinate reference systems"/>
      <project name="crs-conversion-service" description="CRS conversion"/>
    </reference-services>

    <ddms-services>
      <project name="rafs-ddms-services" description="R&D data management"/>
      <project name="eds-dms" description="Engineering data management"/>
    </ddms-services>

    <workflow-processing>
      <project name="ingestion-workflow" description="Data ingestion pipelines"/>
      <project name="indexer-queue" description="Indexing queue management"/>
      <project name="notification" description="Event notifications"/>
      <project name="segy-to-mdio-conversion-dag" description="Seismic format conversion"/>
    </workflow-processing>

    <infrastructure>
      <project name="infra-azure-provisioning" description="Azure infra provisioning"/>
      <project name="os-core-common" description="Shared core libraries"/>
      <project name="os-core-lib-azure" description="Azure-specific libs"/>
    </infrastructure>

    <other-services>
      <project name="geospatial" description="Geospatial services"/>
      <project name="policy" description="Policy engine"/>
      <project name="secret" description="Secret management"/>
      <project name="open-etp-client" description="ETP protocol client"/>
      <project name="schema-upgrade" description="Schema migration tools"/>
    </other-services>

    <cloud-providers>
      <provider code="azure" name="Microsoft Azure"/>
      <provider code="aws" name="Amazon Web Services"/>
      <provider code="gcp" name="Google Cloud Platform"/>
      <provider code="ibm" name="IBM Cloud"/>
      <provider code="cimpl" name="CIMPL (Venus) provider"/>
    </cloud-providers>
  </available-projects>

  <prerequisites>
    <requirement>osdu-quality CLI installed: uv tool install git+https://community.opengroup.org/danielscholl/osdu-quality.git</requirement>
    <requirement>GitLab authentication (choose one):
      - GITLAB_TOKEN environment variable, OR
      - glab CLI authenticated (glab auth login)
    </requirement>
    <requirement>Access to OSDU GitLab projects</requirement>
  <