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analytics-engineering

Analytics-engineering team — 3 agents (analytics-engineer, semantic-layer-engineer, data-quality-testing-engineer) for the TRANSFORMATION layer in the modern data stack: dbt modeling (staging -> intermediate -> marts, the medallion/Kimball split, incremental models, materializations), a governed semantic/metrics layer (one definition of revenue/active-user, metrics-as-code) so every tool agrees, and data quality (dbt tests, freshness, model contracts, anomaly checks) that gates the warehouse. Warehouse-neutral (Snowflake/BigQuery/Redshift/Databricks). 5 skills, a decision-tree knowledge bank (materialization + model-layer trees + a dated 2026 map), 12 best-practices, 4 templates, 4 commands, 1 advisory hook. Distinct from data-platform (ingestion/warehouse/BI) and database-engineering (OLTP). Seams: ELT/warehouse provisioning -> data-platform, OLTP -> database-engineering, BI -> tableau/data-platform, enterprise lakehouse -> microsoft-fabric. Requires ravenclaude-core@>=0.7.0.

Publisher marketplaceanalytics-engineering@ravenclaude · marketplace and plugin share one repository (mcorbett51090/ravenclaude)

npx claudepluginhub mcorbett51090/ravenclaude --plugin analytics-engineering

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What's Inside

Slash Commands4

Steps

/add-data-tests

Add dbt tests, source freshness, model contracts, and anomaly checks that gate the warehouse.

Steps

/define-metrics

Define metrics once in the semantic layer with explicit grain and filters; expose one contract to BI.

Steps

/model-in-dbt

Build layered dbt models (staging/intermediate/marts) with the right materializations and correct incremental logic.

Steps

/refactor-dbt-project

Refactor a messy dbt project into clean layers with restored lineage and right-sized materializations.

Agents3

analytics-engineer

/analytics-engineer

Use for dbt modeling: staging -> intermediate -> marts layering, materialization choice (view/table/incremental), correct incremental models (unique key, is_incremental, late-data), Kimball facts/dims vs OBT, and warehouse-aware SQL. Routes ingestion and metrics to semantic-layer-engineer.

data-quality-testing-engineer

/data-quality-testing-engineer

Use for transform-layer data quality: dbt tests (not_null/unique/accepted_values/relationships), source-freshness gating, model contracts at consumer boundaries, custom tests for business invariants, anomaly detection. Gates the warehouse in CI. Stats → applied-statistics; CI wiring → devops-cicd.

semantic-layer-engineer

/semantic-layer-engineer

Use for the semantic/metrics layer: one governed definition per metric (metrics-as-code via dbt Semantic Layer/MetricFlow), explicit grains and filters, entity/dimension modeling to prevent fan-out/double-counting, and a single BI-facing contract that ends metric drift. Sits on the marts.

Skills5

incremental-model-patterns

/incremental-model-patterns

Build reliable incremental dbt models: choose the right unique_key and strategy (append, merge, delete+insert), handle late-arriving data and out-of-order events, write a safe is_incremental filter, and design the full-refresh fallback — so the model is idempotent from day one.

data-quality-testing

/data-quality-testing

Keep the warehouse trustworthy: dbt tests (not_null/unique/accepted_values/relationships) gating the build in CI, source-freshness checks, model contracts at consumer boundaries, singular tests for business invariants, and anomaly detection beyond schema tests.

dbt-ci-governance

/dbt-ci-governance

Design a dbt CI pipeline that gates every pull request: compile, run, test, and check source freshness in an isolated developer schema; enforce model contracts on published marts; run slim CI on changed models only using dbt state comparison; and block merges on test failures or contract violations.

dbt-modeling

/dbt-modeling

Model in dbt across staging -> intermediate -> marts layers, choose materialization (view/table/incremental) by the trade, write correct incremental models (reliable unique key, is_incremental filter, late-data strategy), and keep it DRY with refs/sources/macros.

semantic-metrics-layer

/semantic-metrics-layer

Build a governed semantic/metrics layer: define each metric once as metrics-as-code (dbt Semantic Layer/MetricFlow) with explicit grain and filters, model entities/dimensions to prevent fan-out, and expose one contract every BI tool consumes — ending metric drift.

Hooks1

Event Hooks

File writes

1 hook across 1 event

Stats

Version0.3.6

LanguageHTML

Stars4

Forks1

MaintenanceExcellent

LicenseMIT

Last CommitJul 15, 2026

AddedJul 19, 2026

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Available In

ravenclaude4

Safety Signals

Caution

Modifies files

Hook triggers on file write and edit operations

Uses power tools

Uses Bash, Write, or Edit tools

README

🐦‍⬛ RavenClaude

A private Claude Code plugin marketplace — bundled team rules, specialist agents, dispatch playbooks, and templates that travel with you across projects.

🚀 ▶ See what RavenClaude is (pitch.html) — the one-page pitch: the value prop, the proof, and the plugin catalog at a glance. Start here. (Or view the raw HTML source, or download and open locally — no server, no build step.)

🏠 ▶ Open the landing page (index.html) rendered in your browser — the front door: a navigable home with the plugin catalog, the specialist roster, and a comfort-posture starter. Regenerated from the manifests on every release.

(Or view the raw HTML source, or download and open locally — no server, no build step.)

🎛 ▶ Open the RavenClaude dashboard — point-and-click editor for your .ravenclaude/comfort-posture.yaml: set per-tool file, network, shell, and package autonomy across three levels (deny → ask → allow) — per layer (user / local / project) and per individual permission — without editing YAML by hand. (That link is the published, read-only preview; to use it for real — where Save & apply writes your repo's config — run rc dashboard from your project, the one canonical launcher across Claude Code, Copilot CLI, and a bare terminal.)

🖥 Working on this repo? Launch the functional local dashboard (where Save & apply actually writes this repo's config) with one command: bash scripts/open-dashboard.sh. It kills any running dashboard server, starts a fresh one, and opens it in your browser automatically. (VS Code users: a .vscode/tasks.json wired as the default build task — Ctrl/Cmd+Shift+B — runs the same script; .vscode/ is gitignored, so add it locally if you want the keybinding.)

📖 ▶ Open the RavenClaude portal — one self-contained page: browse every plugin, agent, skill, hook, rule, and template in the Marketplace section (with an “I want to…” use-case lookup), tune the comfort-posture Dashboard, and more. Regenerated from the manifests on every release.

(Or view the raw HTML source, or download and open locally — no server, no build step.)

🚀 ▶ First Workflow in 10 Minutes — install → dashboard → one governed multi-agent dispatch → /wrap. The canonical onboarding walkthrough. Start here if you've never used RavenClaude before.

🌐 ▶ Raven Power ↗ — the consulting front door behind RavenClaude. This marketplace is the proof-of-craft; the website is where the engagements live.

Today this marketplace ships 164 plugins:

ravenclaude-core — domain-neutral Team Lead + 14 specialists (architect, coders, reviewers, designer, documentarian, deep-researcher, project-manager, partner-success-manager, prompt-engineer, data-engineer, etc.), plus dispatch playbooks (with a Cross-plugin dispatch section), gates, 43 skills, 16 hooks, templates, and the cross-project contribution-staging loop.
power-platform — 11 Microsoft Power Platform specialists (Power Fx, flows, Power BI, Dataverse, model-driven, PCF, Copilot Studio, Power Pages, admin, ALM, tester), 21 skills, an advisory house-opinions hook covering 8 checks, and the bundled pbix-mcp MCP server.
finance — 7 corporate-finance & FP&A specialists (FP&A analyst, financial modeler, controller, treasury, valuation, audit-prep, board-pack composer), 9 skills, templates, advisory anti-pattern hook.
regulatory-compliance — 12 financial-regulatory specialists (6 function: AML/KYC, regulatory reporting, risk-and-controls, policy & procedure writer, examination prep, Bermuda-insurance; plus 6 jurisdiction: BMA, CIMA Cayman, Bahamas, Channel Islands, UK PRA, US), 10 skills, templates, defensive PII-scrub hook.
web-design — 7 web specialists (web architect, UX, visual, frontend implementer, content strategist, accessibility auditor, performance engineer) with WCAG 2.2 AA/AAA, Core Web Vitals, SEO/AEO, and Fluent + React discipline. 11 skills, templates, advisory web anti-pattern hook.
edtech-partner-success — 6 K-12 EdTech partner-success specialists (partner-success manager, success-playbook designer, learning-analytics analyst, QBR composer, partner-profile curator, FERPA comms translator) with 16 skills and a knowledge bank of operating cadences.

View full README on GitHub

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v0.1.1

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Corporate finance & FP&A specialist team — FP&A analyst, financial modeler, controller, treasury analyst, valuation analyst, audit-prep specialist, and board-pack composer. Ships 23 skills including the controller-autopilot: a governed close-to-report cycle (GAAP statements, COA mapping, reconciliation auto-match, review→approve→lock workflow, ELT staging, consolidation, per-entity dashboard, close schedules) plus its live-integration tier (multi-currency remeasurement + CTA, OAuth GL connectors + drill-through lineage, warehouse/RLS dashboard, IdP-backed segregation of duties) and a gold-standard NetSuite close (OAuth2 M2M + SuiteQL BS/IS trial balance, COA-draft, tie-out doctor, changed-after-sign-off drift, layperson runbook). 10 templates, a knowledge bank, and 2 advisory hooks (anti-patterns + secrets/PII scan). Inherits ravenclaude-core protocols (Grounding, Structured Output, Cited-Adjudicator).

v0.18.3

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Power Platform specialist team — 11 agents (incl. power-platform-tester, power-bi-engineer) and 23 skills, with strong ALM/git coverage for solutions, flows, and PBIP. A house-opinions hook flags 8 §3/§4 violations; the knowledge bank carries production decision trees (PA-flow recovery, Dataverse token-acquisition, PCF React surface, PBI deploy/refresh, custom-connector build-path, PBIR Enhanced infinite-spinner debug + full build reference, DAX silent-zero scoring via the `Domain` pattern, sempy.fabric notebook reference, Power BI Copilot report-readiness, Code Apps connector gotchas, PBIP deployment variables + #839, PBIR reference enrichment, PBIP report fast-solve triage router [MCP-optional]) plus a real-engagement scenarios bank. Bundles the community pbix-mcp server (d0nk3yhm/pbix-mcp, MIT) for .pbix/.pbit read/write/DAX-eval (`pip install pbix-mcp`); documents (not bundles) the official Microsoft Dataverse MCP (CLAUDE.md §9a). Extends ravenclaude-core.

v0.44.7

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Project & delivery management team — four specialists across the predictive (PMBOK/PMP) and agile (Scrum/Kanban) tracks and the hybrid between: delivery-lead (charter, schedule, scope/change control, earned value), scrum-master (backlog, sprints, ceremonies, velocity, impediments), risk-and-raid-analyst (scored qual+quant risk, RAID depth, mitigation/contingency, issue triage), and stakeholder-comms-lead (stakeholder register, comms plan, status/exec reporting, escalation memos, steering packs). Deepens — does NOT replace — ravenclaude-core's domain-neutral project-manager (the lightweight RAID/status-hygiene default every plugin routes to); this is the deep PM craft layer. Knowledge: a predictive-vs-agile-vs-hybrid decision tree + a best-practices library. Seams: prose polish → ravenclaude-core/documentarian; system design → architect. Requires ravenclaude-core@>=0.7.0.

v0.4.1

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AI/LLM red-teaming team — 2 agents (ai-redteam-lead, adversarial-testing-engineer) for the layer answering 'can this AI system be made to do harm, leak data, or exceed its authority — and how do we harden it?': threat modeling + rules of engagement, the attack taxonomy (OWASP LLM Top 10 2025 + MITRE ATLAS), direct vs indirect prompt injection, jailbreaks (roleplay/encoding/many-shot/crescendo), data exfiltration & training-data extraction, agentic tool-abuse / excessive agency, multimodal attacks, and defense-in-depth remediation. Fluent in automated red-team harnesses (PyRIT, Garak, Promptfoo red-team, Giskard) and likelihood×impact severity. 3 skills, a 2-doc knowledge bank (attack-taxonomy decision tree + 2026 patterns), and 2 templates. Distinct from llm-evaluation-engineering (quality-regression eval), trust-and-safety (content-moderation / T&S policy), and security-engineering (app/infra pentest) — the adversarial AI-security layer over model- and agent-based systems. Requires ravenclaude-core@>=0.7.0.

v0.2.0

mcorbett51090

analytics-engineering

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README

🐦‍⬛ RavenClaude

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