• Current Status
• Build Table — sorted newest → oldest
• Incidents — sorted newest → oldest, with Incident #1 being the most recent
• Top Failure Reasons
• Suggested Next Step

Use the chat reply to summarize the report, not to replace it.

Prerequisites

• Azure CLI (az) installed and authenticated (az login)
• Node.js on PATH
• Network access to dev.azure.com (the fetch script calls Azure DevOps REST APIs)

Shared Setup

The scripts live inside this skill directory at <skill-dir>/scripts/. Always invoke them by absolute path. Derive <skill-dir> from the absolute path of this SKILL.md.

Use these defaults unless the user asks for something else:

OUT_DIR=/tmp/build-health
REPORT_FILE="$OUT_DIR/build-health-report.md"

1. Fetch Build Data

Run the fetch script from this skill directory. It downloads builds, timelines for failed builds, and log tails for failing test/compile tasks — all in parallel batches.

bash <skill-dir>/scripts/fetch-builds.sh --count 100 --out "$OUT_DIR"

Options:

• --count N — Number of recent builds to fetch (default: 100)
• --out DIR — Output directory (default: ./build-data)
• --pipeline ID — Pipeline definition ID (default: 111)
• --branch NAME — Branch to filter (default: main)

Run this in a terminal with mode=sync and a generous timeout (e.g. 300000ms). The script needs network access, so request unsandboxed execution if sandboxing is enabled.

2. Analyze the Data

Once the data is downloaded, always generate the markdown report file first:

node <skill-dir>/scripts/analyze-builds.mjs "$OUT_DIR" --format markdown --report "$REPORT_FILE"

This runs entirely offline against the downloaded data and produces a predictable artifact that the user can open and consume directly.

If you need a terminal-friendly version for yourself while working, optionally run:

node <skill-dir>/scripts/analyze-builds.mjs "$OUT_DIR" --format text

The markdown report includes:

1. Per-build status — Each build with pass/fail, failure reasons, error excerpts, and commit links
2. Break/fix transitions — When the build went red, when it recovered, how long each incident lasted
3. Error details — Actual error messages from test logs (not just "exited with code 1")
4. Commit links — GitHub compare URLs between the last green and first red build
5. Summary — Overall success rate, top failure reasons, current build status

Workflow 1: Build Is Red Right Now

1. Fetch the last 100 builds and generate the markdown report file.
2. Read the report first. Do not guess the culprit yet.
3. Summarize these points in chat:
   • Whether the latest build is still red
   • Which build was the first red build in the current incident

…

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