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lmiranda 2d51df7a42 feat(marketplace): command consolidation + 8 new plugins (v8.1.0 → v9.0.0) [BREAKING]

Phase 1b: Rename all ~94 commands across 12 plugins to /<noun> <action>
sub-command pattern. Git-flow consolidated from 8→5 commands (commit
variants absorbed into --push/--merge/--sync flags). Dispatch files,
name: frontmatter, and cross-reference updates for all plugins.

Phase 2: Design documents for 8 new plugins in docs/designs/.

Phase 3: Scaffold 8 new plugins — saas-api-platform, saas-db-migrate,
saas-react-platform, saas-test-pilot, data-seed, ops-release-manager,
ops-deploy-pipeline, debug-mcp. Each with plugin.json, commands, agents,
skills, README, and claude-md-integration. Marketplace grows from 12→20.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

2026-02-06 14:52:11 -05:00

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name, description, arguments

name

description

arguments

data review

Audit data integrity, schema validity, and dbt compliance

name	description	required
path	File, directory, or dbt project to audit	true

/data review

Comprehensive data integrity audit producing a detailed report with findings at all severity levels. For human review and standalone codebase auditing.

Usage

/data review <path>

Examples:

/data review ./dbt/
/data review ./portfolio_app/toronto/
/data review ./dbt/models/marts/

What It Does

Activates the data-advisor agent in review mode
Scans target path to determine scope:
- Identifies dbt project files (.sql models, schema.yml, sources.yml)
- Identifies Python files with database operations
- Identifies migration files
- Identifies PostGIS usage
Runs all check categories:
- Schema validity (PostgreSQL tables, columns, types)
- dbt project health (parse, compile, test, lineage)
- PostGIS compliance (SRID, geometry types, extent)
- Data type consistency
- Code patterns (unsafe SQL, hardcoded queries)
Produces detailed report with all severity levels (FAIL, WARN, INFO)
Provides actionable recommendations for each finding

Output Format

+----------------------------------------------------------------------+
|  DATA-PLATFORM - Data Integrity Audit                                 |
|  /path/to/project                                                     |
+----------------------------------------------------------------------+

Target: /path/to/project
Scope: N files scanned, N models checked, N tables verified

FINDINGS

FAIL (N)
  1. [location] violation description
     Fix: actionable fix

WARN (N)
  1. [location] warning description
     Suggestion: improvement suggestion

INFO (N)
  1. [location] info description
     Note: context

SUMMARY
  Schema:   Valid | N issues
  Lineage:  Intact | N orphaned
  dbt:      Passes | N failures
  PostGIS:  Valid | N issues | Not applicable

VERDICT: PASS | FAIL (N blocking issues)

When to Use

Before Sprint Planning

Audit data layer health to identify tech debt and inform sprint scope.

/data review ./dbt/

During Code Review

Get detailed data integrity findings alongside code review comments.

/data review ./dbt/models/staging/stg_new_source.sql

After Migrations

Verify schema changes didn't break anything downstream.

/data review ./migrations/

Periodic Health Checks

Regular data infrastructure audits for proactive maintenance.

/data review ./data_pipeline/

New Project Onboarding

Understand the current state of data architecture.

/data review .

Severity Levels

Level	Meaning	Gate Impact
FAIL	Blocking issues that will cause runtime errors	Would block `/data gate`
WARN	Quality issues that should be addressed	Does not block gate
INFO	Suggestions for improvement	Does not block gate

Differences from /data gate

/data review gives you the full picture. /data gate gives the orchestrator a yes/no.

Aspect	/data gate	/data review
Output	Binary PASS/FAIL	Detailed report
Severity	FAIL only	FAIL + WARN + INFO
Purpose	Automation	Human review
Verbosity	Minimal	Comprehensive
Speed	Fast (skips INFO)	Thorough

Use /data review when you want to understand. Use /data gate when you want to automate.

Requirements

data-platform MCP server must be running
For dbt checks: dbt project must be configured (auto-detected via dbt_project.yml)
For PostgreSQL checks: connection configured in ~/.config/claude/postgres.env

Graceful degradation: If database or dbt unavailable, applicable checks are skipped with a note in the report rather than failing entirely.

Skills Used

skills/data-integrity-audit.md - Audit rules and patterns
skills/mcp-tools-reference.md - MCP tool reference

/data gate - Binary pass/fail for automation
/data lineage - Visualize dbt model dependencies
/data schema - Explore database schema

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