Pipeline Health Report

Produce an actionable daily health report for Maestro data workflows using Kragle MCP tools.

Configuration

See _shared/report-config.md for the standard config resolution pattern.

Config schema (~/.claude/skills/pipeline-health-report/config.json):

• owner: workflow owner pattern string (e.g., data.eng.myteam)
• workflow_id_pattern: wildcard pattern string (e.g., DSE.BILLING.*)
• workflow_ids: list of explicit workflow ID strings
• cluster: "prod" or "sandbox" (default: "prod")
• limit: max workflows to check (default: 50)

Required scope: at least one of owner, workflow_id_pattern, or workflow_ids.

Arguments

Parse from user input, falling back to config.json:

• owner: workflow owner pattern — e.g. data.eng.*
• workflow_id_pattern: wildcard pattern — e.g. DSE.BILLING.*
• workflow_ids: explicit list of workflow IDs to check
• cluster: prod | sandbox (default: prod — never default to sandbox for health reports)
• limit: max workflows to check (default: 50)

Workflow

1. Discover workflows. Use the configured scope to find workflows:
   • If workflow_ids is set: skip search, check each ID directly via get_latest_instance
   • If workflow_id_pattern is set: call search_workflows with workflow_id_pattern and cluster=prod
   • If owner is set: call search_workflows with owner and cluster=prod
   • If none is set and no config.json: ask the user once, then save their answer to config.json for future runs
2. Check every workflow. For EACH workflow returned, call get_latest_instance with cluster=prod. Record status: SUCCEEDED, FAILED, IN_PROGRESS, or no recent instance.
3. Drill into failures. For every FAILED instance, call get_instance_failures with cluster=prod. Extract: step_id, attempt number, status, and instance link. This step is MANDATORY — never report a failure without step-level detail.
4. Check running durations. For every IN_PROGRESS instance, call get_instance_summary with cluster=prod. Flag any instance running longer than 2 hours as "long-running."
5. Generate report. Output markdown with these sections in order:

## Pipeline Health Report — {date}
Cluster: {cluster} | Owner filter: {owner or "all"} | Workflows checked: {N}

### Summary
- Failed: {count} | In Progress: {count} | Succeeded: {count} | No Recent Run: {count}

### Failed Workflows
(For each: workflow_id, failed step, error summary, instance link)

### Long-Running Workflows
(For each: workflow_id, duration so far, instance link)

### In Progress
(Compact list: workflow_id, start time)

### Recently Succeeded
(Compact table: workflow_id, last success time)

6. Deliver as HTML. Follow the shared HTML delivery pattern in _shared/html-delivery.md. Report name: pipeline-health. TLDR includes workflows checked, failure count, and long-running instances.
7. Terminate. Report is complete when all sections are populated (even if a section says "None").

Design Principles

1. Team-level only. Aggregate to team level — it is the right granularity for a periodic digest. Individual-level detail (commits per person, PR count per author) is too noisy for a team report.
2. Deterministic math first, LLM narrates only. All classification (severity, flaky vs broken, pass/fail) must be computed deterministically from data. The LLM writes prose around the numbers but never assigns severity or makes classification judgments.
3. Pair metrics with counter-metrics. Never report velocity without stability. If showing deploy frequency, also show change failure rate. If showing PR throughput, also show rework rate.

Golden Rules

1. Always cluster=prod. Every Kragle MCP call passes cluster="prod" unless the user explicitly says sandbox. Sandbox workflows are tests, not production health.
2. Never skip get_instance_failures. Every FAILED workflow gets a get_instance_failures call. "Workflow X failed" without step detail is useless.
3. Check ALL workflows, not a sample. If search_workflows returns 50 results and you set limit=50, consider whether there are more. Increase limit or paginate.
4. Failures first. Report sections are ordered by severity. Failures at top, succeeded at bottom.
5. Include links. Every failed or in-progress workflow includes its instance_link from the API response. The reader must be able to click through without additional lookups.
6. "All clear" is still a report. When everything succeeded, produce the full report structure with counts and timestamps. One sentence is not a report.
7. No invented data. Every number in the report comes from a Kragle API response. Never estimate or infer workflow counts.

Anti-Rationalization Counter-Table

Termination Labels

Self-Review Checklist

Before delivering the report, verify:

• Every Kragle call used cluster="prod" (or user-specified cluster)
• Total workflows in Summary matches count from search_workflows
• Every FAILED workflow has get_instance_failures output (step_id + link)
• Every IN_PROGRESS workflow has duration from get_instance_summary
• Failed section appears before Succeeded section
• Instance links are present for all failed and in-progress workflows
• Report has a date header and owner filter noted
• HTML version uploaded to S3 with commuter link (unless --no-html or upload failed with noted fallback)
• Slack/chat delivery uses TLDR + link, not the full report