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Review code and data pipeline changes for correctness, security, performance, maintainability, contract breaks, and missing verification. Use before merge, after implementation, for PRs, commits, pending diffs, or codebase risk scans.
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Baseado na classificação ocupacional SOC
| name | code-review |
| description | Review code and data pipeline changes for correctness, security, performance, maintainability, contract breaks, and missing verification. Use before merge, after implementation, for PRs, commits, pending diffs, or codebase risk scans. |
Review adversarially. Findings require evidence from code, diff, tests, or runtime behavior.
--pending: review staged and unstaged changes.codebase: scan broader architecture/risk surface.Lead with findings:
Findings:
- [Critical|High|Medium|Low] file:line - issue, impact, evidence, fix
Open questions:
- ...
Summary:
- Reviewed: <scope>
- Verification observed: <commands/results or missing>
Build and maintain an internal technical LLM wiki when the user requests wiki work or a verified major or architectural change qualifies for automatic wiki review. Use for project memory, architecture notes, contracts, runbooks, decisions, glossary, incremental ingest, delta status, and wiki health. Do not use merely because a routine task or plan completed.
Explore ambiguous ideas and solution directions before evidence-backed research or implementation planning. Use for ideation, framing, assumption checks, option generation, product or architecture trade-offs, and deciding whether research or a plan is needed.
Research technical options with source-backed recommendations. Use for technology evaluation, architecture trade-offs, library/framework choices, best practices, scalability, security, maintainability, or when current external facts matter.
Create implementation plans, architecture decisions, and phased roadmaps. Use for Standard or Complex changes, new pipelines, schema changes, migrations, multi-file features, technology choices, or when acceptance criteria and verification strategy are unclear.
Design data ingestion into landing/bronze layers. Use for source onboarding, transfer pattern selection, full/incremental/CDC scope, change detection, landing zones, schema drift, idempotent file or batch processing, and ingestion quality gates.
Design warehouse and semantic data models. Use for grain definition, fact/dimension design, star schema, Kimball, Data Vault, SCD, bridge tables, surrogate keys, semantic metrics, and model review.