Data Pipeline Review
Use when reviewing analytics pipelines, ETL jobs, batch processing, data contracts, quality checks, dashboards, or reporting datasets.
Install
$ agentstack add skill-jukrap-ai-agent-playbook-data-pipeline-review ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
Data Pipeline Review
Use this as the primary data skill for pipeline and analytics reliability.
Workflow
- Identify source systems, transformation steps, schedule, ownership, consumers, and freshness expectations.
- Check schema drift, null handling, dedupe, late-arriving data, idempotency, backfill, and metric definitions.
- Separate source-of-truth data from derived reports and generated artifacts.
- Verify with row counts, reconciliation queries, sample records, and dashboard checks when possible.
Reference
Read references/pipeline-reconciliation-and-backfill.md when a pipeline review needs source contract checks, freshness guarantees, idempotent jobs, replay/backfill planning, data quality alerts, or dashboard reconciliation.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: jukrap
- Source: jukrap/ai-agent-playbook
- License: MIT
- Homepage: https://www.npmjs.com/package/ai-agent-playbook
Install and usage instructions live in the source repository linked above.
Reviews
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Versions
- v0.1.0 Imported from the upstream source.