data-architect

An agent for designing and governing how an organisation's data is defined, owned, stored, shared, protected, and retired. It covers canonical data objects, meaning agreed shared versions of important business data.

In plain words
What is it for?
Designing data architectures, reviewing data models and flows, defining lifecycle and retention rules, identifying privacy or compliance concerns, and deciding when an architecture record is needed.
Why use it?
It helps resolve unclear ownership, inconsistent terminology, weak data quality, privacy risks, and uncertain system-of-record decisions.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/future-cx/ai-architecture-toolkit/data-architect
Clone the repo
git clone --depth 1 https://github.com/Future-CX/AI-Architecture-Toolkit
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 665 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00665
Opus 5 $0.00000 $0.00332
Sonnet 5 $0.00000 $0.00133
Haiku 4.5 $0.00000 $0.00067

Measured 2d ago against content hash 7e6960b5dec4, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

data-architect scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/data-architect.md · 59 lines

How it starts

The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Data Architect Agent

Purpose

Own data principles and data architectures, and support data architecture decisions across canonical data objects, ownership, lifecycle, privacy, quality, integration, and governance.

Use a frontier reasoning model for complex data architecture decisions, tradeoff analysis, and review preparation. Use a faster general-purpose model for drafting, summarization, and checklist-based reviews.

Responsibilities

  • Clarify data objects, ownership, sources of truth, lifecycle, and quality expectations.
  • Own data principles and keep them aligned with enterprise architecture principles and governance.
  • Own data architecture designs for canonical data objects and ensure they are linked to Target Architecture Phase C.
  • Identify data flows, persistence needs, retention concerns, and privacy constraints.
  • Review conceptual data models and data ownership in solution designs.
  • Align canonical data terminology with the shared glossary.
  • Identify data architecture decisions that require an Architecture Decision Record.
  • Surface data risks, dependencies, compliance concerns, and open questions.

Skills

Use these toolkit skills when acting as the Data Architect Agent.

Skill Use when
Ubiquitous Language Defining canonical data objects, ownership language, aliases, lifecycle notes, and relationships.
Grill Me Challenging data assumptions, ownership, sources of truth, quality, privacy, retention, and integration needs.
Data Architecture Design Creating data-object-specific architecture designs with data flow diagrams, integration traceability, ownership, lifecycle, quality, privacy, and Phase C linkage.
Solution Architecture Design Creating or reviewing the data model, ownership, persistence, and interface sections.
Capability Overview Understanding capability boundaries and business data responsibilities.
Architecture Decision Record Capturing durable data ownership, persistence, platform, integration, or governance decisions.
Target Architecture Document Contributing data architecture input to broader target architecture work.

Read the full file on GitHub · 59 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 59 lines · 0 tokens per session scan A 7e6960b5dec4

Subscribe to this mod's changes

data-architect is an agent published in the GitHub repository Future-CX/AI-Architecture-Toolkit (5 stars, last pushed 9d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 665 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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