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Masthead Agent Plugins & Skills

A unified, multiplatform agent toolkit for Masthead Data — BigQuery data observability and FinOps cost optimization for Google Cloud.

This repository provides single-source-of-truth plugins and skills for:

  • Claude Code
  • OpenAI Codex
  • Antigravity / Gemini CLI
  • Universal Skills CLI

Core Capabilities

  1. FinOps (Cost Savings): Optimize BigQuery compute, storage, data models, and pipelines based on historical dataset insights.
  2. Real-Time Observability: Connect via Model Context Protocol (MCP) to investigate, trace lineage, and resolve live pipeline failures and data anomalies.

Safety Framework: Cautious Advisory (Non-Action)

All FinOps skills adhere to strict non-action principles:

  • Zero Automated Mutations: The agent never executes destructive commands (bq rm), alters billing configurations (bq update), or disables running pipelines directly.
  • Decision Support & Artifacts: The agent investigates recency, analyzes lineage and downstream impact, provides clear cost/risk trade-offs, and generates whatever review artifacts the human operator requests (Markdown review tables, CSV candidate exports, or standalone shell scripts with dry-run commands for the user to inspect and run).

Slash Commands

The plugin ships two workflows. Names differ per client:

Workflow Claude Code Codex Antigravity
Incident triage — open incidents, upstream lineage, blast radius, mitigation plan /masthead-agent-tools:triage $masthead-agent-tools:masthead-triage /masthead-triage
FinOps audit — dead-end and unused tables, dataset billing models, pipelines, data models /masthead-agent-tools:savings $masthead-agent-tools:masthead-savings /masthead-savings

Both accept an optional scope after the name, for example … savings tables in project my-project, … savings datasets, … triage incident <uuid>, … triage table project.dataset.table.


For coding agents: setup checklist

If you are an AI coding agent asked to set up Masthead tools, do exactly this:

  1. Detect which client you are running in (Claude Code, Codex, Antigravity) and follow only that subsection under Installation.
  2. Plugins load at startup. After installing, stop and tell the user to restart the client.
  3. The masthead MCP server needs a one-time browser sign-in the user must do: Claude Code /mcp → authenticate masthead; Codex codex mcp login masthead; Antigravity Agent Settings → Customizations → masthead → Authenticate. A 401 Unauthorized from any tool means this step is missing.
  4. Tell the user the first command to run after restart: the triage workflow works for every tenant; the FinOps workflow additionally needs the BigQuery insights export enabled (the skill checks this via get_tenant_settings and stops with a link if it is not).
  5. Do not run any workflow in the session that installed the plugin — it cannot see the plugin yet.

Installation

1. Claude Code

Add the Masthead marketplace and install the plugin:

/plugin marketplace add masthead-data/for-agents
/plugin install masthead-agent-tools@masthead-data
/reload-plugins

For local development from a cloned repository:

claude plugin marketplace add ./
claude plugin install masthead-agent-tools@masthead-data

2. OpenAI Codex CLI

Add the marketplace and install via Codex CLI:

codex plugin marketplace add masthead-data/for-agents
codex plugin add masthead-agent-tools@masthead-data

Or interactively inside Codex via /plugins.

3. Google Antigravity & Agent Plugins (1.0.0)

This repository adheres to the vendor-neutral Agent Plugins 1.0.0 specification.

To add this plugin to Antigravity:

  • Workspace Level: Clone into your project's .agents/plugins/:

    git clone https://github.com/masthead-data/for-agents.git .agents/plugins/masthead-agent-tools
  • Global Level: Make it available across all workspaces by placing it in ~/.gemini/config/plugins/:

    git clone https://github.com/masthead-data/for-agents.git ~/.gemini/config/plugins/masthead-agent-tools

4. Universal Skills CLI

Install individual skills or the full suite directly into any project:

# Install all skills
npx skills add masthead-data/for-agents

# Or install a specific skill
npx skills add masthead-data/for-agents --skill masthead-storage-savings-with-tables

Prerequisites & Authentication

  • Masthead Account & Dataset: A provisioned Masthead insights dataset in BigQuery. Request access →
  • Google Cloud CLI: Authenticated via gcloud auth login with BigQuery read permissions.
  • MCP Server Authentication: The Masthead MCP server (https://mcp.mastheadata.com/mcp) authenticates via Google OAuth 2.0 in your agent client — see the setup checklist above for the per-client command (service account support coming soon).

FinOps skills resolve your insights dataset through the get_tenant_settings MCP tool (dataset name, export enabled flag, look-back window). Without MCP, set MASTHEAD_INSIGHTS_DATASET or put the dataset into ~/.masthead/config.json / .masthead/config.json; the skill asks once otherwise.


Available Skills

Skill Category Mode Description
masthead-incident-triaging Observability MCP Triage, trace upstream/downstream lineage, assign ownership, and manage live incidents.
masthead-asset-prioritization Observability MCP Propose PRIORITY/CRITICAL (or REGULAR) tiers for tables and BI assets from asset scores, with reasons; apply on confirmation.
masthead-storage-savings-with-tables FinOps Local SQL Identify and clean up dead-end and unused BigQuery tables.
masthead-storage-savings-with-datasets FinOps Local SQL Optimize dataset-level billing models (logical vs. physical) and partition expiration.
masthead-compute-savings-with-workload-assignments FinOps Local SQL Rebalance Dataform, dbt, and Airflow model compute between reservations and on-demand.
masthead-compute-savings-with-pipelines FinOps Local SQL Detect and pause legacy, orphaned, or inefficient data pipelines.

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About

A curated collection of Agent Skills for working with Masthead Data — BigQuery cost observability and FinOps for Google Cloud. These skills help AI agents understand BigQuery slot economics, reservation strategies, and cost optimization workflows more accurately and efficiently.

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