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    CI Failure Root-Cause Packager

    1

    Turn massive CI logs and scattered artifacts into a compact failure bundle with the probable first causal error, cascade analysis, candidate files, and focused reproduction commands.

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    CI Failure Root-Cause Packager

    CI Failure Root-Cause Packager

    Example session with this skill installed

    Analyze this failed CI run and package the probable root cause.

    CI artifacts
    ./ci-run-export/

    Repository
    ./

    Requirements

    • recursively inspect logs, test output, artifacts, and trace-adjacent files;
    • normalize ANSI codes and repeated CI noise;
    • identify structured error events in temporal order;
    • distinguish the first probable causal error from cascade failures;
    • correlate compiler errors, test setup failures, assertions, service errors, and browser/test-runner output;
    • map evidence to repository files when possible;
    • identify candidate files to inspect first;
    • generate the smallest safe reproduction command using the repository's existing test/build tooling;
    • classify confidence as HIGH, MEDIUM, or LOW;
    • detect likely infrastructure-root-cause failures separately from application-code failures;
    • flag retry/flaky behavior when evidence supports it;
    • redact likely secrets from generated reports but do not modify the original artifacts;
    • do not patch source code automatically;
    • generate failure_bundle.md, reproduction commands, normalized events, candidate files, evidence snippets, and a JSON summary.
    • Read your context and instructions
    • Compiled the ci failure root-cause
    • Generated the data export

    CI root-cause package complete

    CI sources analyzed
    14

    Raw log lines scanned
    10,842

    Structured error events extracted
    67

    Probable root-cause confidence
    HIGH

    First causal error

    Category
    TEST_SETUP

    Source
    artifacts/api-integration.log:418

    File
    tests/fixtures/postgres.ts:72

    Message
    Database fixture failed readiness check after 30 seconds: ECONNREFUSED 127.0.0.1:5432

    Why this is probably causal

    The database fixture failure occurred before:

    • 11 API test timeouts
    • 18 browser assertion failures
    • 6 Playwright locator timeouts
    • job cancellation summaries

    All downstream failures depend on the same unavailable integration database.

    Cascade cluster

    Root
    Postgres test fixture failed to become ready

    Cascade

    1. API bootstrap failed
    2. authentication setup timed out
    3. Playwright login step timed out
    4. checkout integration tests failed
    5. downstream test matrix was canceled

    Cascade events linked
    41

    Candidate files

    1. tests/fixtures/postgres.ts
      Evidence confidence: HIGH

    2. docker-compose.test.yml
      Evidence confidence: HIGH

    3. tests/global-setup.ts
      Evidence confidence: MEDIUM

    4. playwright.config.ts
      Evidence confidence: LOW

    Focused reproduction

    pnpm test:integration tests/api/checkout.test.ts

    If the database fixture still fails

    docker compose -f docker-compose.test.yml up postgres

    Then rerun

    pnpm test:integration tests/api/checkout.test.ts

    What not to fix first

    Do not start by editing the 18 Playwright assertions.

    Those failures occur after the integration environment is already unavailable.

    Do not increase locator timeouts until the database startup failure is resolved.

    Suggested fix direction

    Inspect the test database startup/readiness path:

    tests/fixtures/postgres.ts
    docker-compose.test.yml

    Verify

    • the container starts successfully;
    • port 5432 is reachable from the test process;
    • readiness waits for the actual database health check;
    • CI runner networking matches the compose configuration.

    Validation sequence

    1. Start the database fixture in isolation
    2. Run the focused checkout API test
    3. Run the Playwright login/checkout tests
    4. Rerun the complete CI job

    Files generated

    • failure_bundle.md
    • failure_summary.json
    • normalized_events.jsonl
    • candidate_files.csv
    • reproduction_commands.md
    • evidence_snippets/first_causal_error.txt

    The bundle identifies the most probable causal failure from the available CI evidence. Validate the proposed reproduction and focused fix before treating downstream errors as independently actionable.

    candidate_files.csv

    CSV · data export

    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.

    About this skill

    The problem

    A failed CI job rarely produces one clean error.

    Developers often have to search through thousands of log lines, test artifacts, browser traces, subprocess output, and secondary failures before finding the one event that actually caused everything else.

    What it does

    CI Failure Root-Cause Packager converts a noisy CI run into a compact debugging package.

    • Ingests logs and exported CI artifacts
    • Removes repeated and low-value noise
    • Extracts structured error events
    • Distinguishes the first probable causal error from downstream cascades
    • Maps evidence to repository files
    • Correlates test, build, service, and browser failures
    • Produces focused reproduction commands
    • Identifies candidate files to inspect first
    • Detects infrastructure-root-cause patterns
    • Flags flaky and retry candidates
    • Redacts likely secrets from generated reports
    • Creates a review-ready failure bundle

    Why this beats prompting it yourself

    A generic prompt can summarize one pasted log.

    This skill correlates multiple CI artifacts and the repository:

    Logs + Artifacts + Traces → Normalize → Causal Clustering → Code Mapping → Reproduction → Failure Bundle

    First causal error, not the last visible error

    A CI run can generate dozens of failures after one fixture, compiler, service, or dependency error.

    The skill prioritizes the first evidence-backed causal failure and groups the rest as downstream symptoms.

    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 any payment.

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    Recently published to Agensi

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    Trust & safety

    Security scanned

    Verified clean 18 days ago

    • Passed all security checks, Safe to install

    Requires

    playwright
    Node.js
    Python
    vitest

    Listed18 days ago

    What's inside

    Frequently Asked Questions