DocsMarkdown Export

Markdown Export

Universal system prompt

Export your blueprint as structured markdown and paste it into any AI system prompt or custom instructions field. Works with every AI platform that accepts text context — no API, no extension required.

Universal format
Works everywhere

Export format

Markdown structure

The exported markdown follows a consistent 4-layer structure that mirrors the blueprint JSON. Each layer is a level-2 heading with its modules as key-value pairs. The format is designed to be both human-readable and maximally parseable by LLMs.

blueprint-export.md
markdown
# AI Identity Blueprint — Alex Chen

> Generated by Artificial ID · v3 · 2026-03-10

---

## Layer 1: Core Identity

**Name:** Alex Chen
**Role:** Senior Full-Stack Engineer
**Communication style:** Direct, precise, context-aware
**Work preferences:** Async-first, documentation-driven, deep focus blocks

---

## Layer 2: Voice & Tone

**Formality:** Semi-formal
**Verbosity:** Concise — prefer bullet points and headers over prose walls
**Humor:** Dry, occasional; never forced
**Preferred format:** Structured with headers; code blocks for all code

---

## Layer 3: Code DNA

**Primary languages:** TypeScript, Python, Rust
**Frameworks:** Next.js (frontend), FastAPI (API), Axum (systems)
**Code style:** Functional where possible, explicit over clever, no magic
**Tools:** Neovim, tmux, Cursor, Warp
**Philosophy:** Boring stack, exotic algorithms. Ship boring, optimize relentlessly.

---

## Layer 4: Knowledge Base

**Domains:** Distributed systems, developer tooling, AI/ML infrastructure
**Reasoning style:** First-principles — strip to axioms before rebuilding
**Mental models:** Second-order effects, Chesterton's fence, inversion
**Known biases:** Bias toward over-engineering; watch for gold-plating

---

*This file was exported from Artificial ID. Re-import or update via the dashboard.*

One file, 4 layers

The export is a single self-contained markdown file. Layers are separated by horizontal rules for clear visual parsing.

Selective layer export

From the dashboard Export tab, choose which layers to include. Exclude Code DNA for non-technical contexts, for example.

Versioned header

Every export includes a version number and date. When you update your blueprint, re-export and replace to keep context current.

ChatGPT

Custom instructions format

ChatGPT custom instructions split into two fields: “What would you like ChatGPT to know about you?” and “How would you like ChatGPT to respond?” Paste your Core Identity and Knowledge Base into the first field, and Voice & Tone into the second.

Field 1: What to know about you
# About me
{{NAME}} — {{ROLE}}

## Background
{{KNOWLEDGE_BASE.DOMAINS}}

## How I work
{{CORE_IDENTITY.WORK_PREFERENCES}}
Field 2: How to respond
Formality: {{VOICE_TONE.FORMALITY}}
Verbosity: {{VOICE_TONE.VERBOSITY}}
Format: {{VOICE_TONE.PREFERRED_FORMAT}}
Humor: {{VOICE_TONE.HUMOR}}

ChatGPT custom instructions character limit

Each field in ChatGPT custom instructions has a 1,500 character limit. The full blueprint export is typically 2,000–3,000 characters. Use selective layer export (Core Identity + Voice only, or Code DNA only) to stay within limits, or use the browser extension which bypasses this restriction by injecting into the system prompt directly.

Claude Projects

Structured identity for Claude

Claude Projects support a project-level system prompt and multiple uploaded knowledge files. The XML-tagged format below works particularly well with Claude's context parsing — Claude is trained to understand XML-structured system prompt data.

Claude Project system prompt (XML format)
xml
<identity>
  <name>{{NAME}}</name>
  <role>{{ROLE}}</role>
  <communication_style>{{CORE_IDENTITY.COMMUNICATION_STYLE}}</communication_style>
</identity>

<voice>
  <formality>{{VOICE_TONE.FORMALITY}}</formality>
  <verbosity>{{VOICE_TONE.VERBOSITY}}</verbosity>
  <format>{{VOICE_TONE.PREFERRED_FORMAT}}</format>
</voice>

<technical_profile>
  <languages>{{CODE_DNA.LANGUAGES}}</languages>
  <frameworks>{{CODE_DNA.FRAMEWORKS}}</frameworks>
  <style>{{CODE_DNA.STYLE}}</style>
  <philosophy>{{CODE_DNA.PHILOSOPHY}}</philosophy>
</technical_profile>

<knowledge>
  <domains>{{KNOWLEDGE_BASE.DOMAINS}}</domains>
  <reasoning>{{KNOWLEDGE_BASE.REASONING_STYLE}}</reasoning>
  <mental_models>{{KNOWLEDGE_BASE.MENTAL_MODELS}}</mental_models>
</knowledge>

Use knowledge files for depth

Upload your full markdown export as a knowledge file in the project. The system prompt stays lightweight (XML tags above) while the knowledge file provides deep context that Claude can reference when needed.

Or use MCP for live sync

Claude Desktop with MCP enabled pulls your blueprint fresh on each conversation — no manual file uploads. Consider MCP if you update your blueprint frequently.

Template variables

Build custom prompts

The dashboard Export tab offers a template mode where you write your own system prompt structure and insert blueprint values using double-brace variables. The template is resolved server-side and returned as a ready-to-paste string.

Template prompt (example)
# Who you're talking to
{{NAME}} — {{ROLE}}

## How I communicate
- Formality: {{VOICE_TONE.FORMALITY}}
- Verbosity: {{VOICE_TONE.VERBOSITY}}
- Format preference: {{VOICE_TONE.PREFERRED_FORMAT}}

## Technical context
Languages: {{CODE_DNA.LANGUAGES}}
Frameworks: {{CODE_DNA.FRAMEWORKS}}
Philosophy: {{CODE_DNA.PHILOSOPHY}}

## What I know deeply
{{KNOWLEDGE_BASE.DOMAINS}}

## How I think
{{KNOWLEDGE_BASE.REASONING_STYLE}}
VariableBlueprint pathExample value
{{NAME}}core_identity.nameAlex Chen
{{ROLE}}core_identity.roleSenior Full-Stack Engineer
{{VOICE_TONE.FORMALITY}}voice_tone.formalitysemi-formal
{{VOICE_TONE.VERBOSITY}}voice_tone.verbosityconcise
{{VOICE_TONE.PREFERRED_FORMAT}}voice_tone.preferred_formatstructured with headers
{{CODE_DNA.LANGUAGES}}code_dna.languages[]TypeScript, Python, Rust
{{CODE_DNA.FRAMEWORKS}}code_dna.frameworks[]Next.js, FastAPI, Axum
{{CODE_DNA.PHILOSOPHY}}code_dna.philosophyBoring stack, exotic algorithms
{{KNOWLEDGE_BASE.DOMAINS}}knowledge_base.domains[]Distributed systems, dev tooling
{{KNOWLEDGE_BASE.REASONING_STYLE}}knowledge_base.reasoning_styleFirst-principles

Token counts

Estimated token usage

These are approximate token counts using the GPT-4 / Claude tokenizer (cl100k_base). Actual counts vary by your content length. Use selective exports to minimize context overhead.

Export scopeApprox. tokensNotes
Full blueprint (all 4 layers)~400–600Default full export
Core Identity + Voice only~150–200Lightweight, style-focused
Code DNA only~100–180For coding assistants
Knowledge Base only~120–200For research / analysis
Single module (e.g. code style)~30–60Surgical precision

For most coding workflows, the Code DNA layer alone (~100–180 tokens) provides the highest signal-to-token ratio. Add Core Identity (+~80 tokens) when the AI needs to know how to address and communicate with you, not just how you code.

Integration patterns

System prompt integration patterns

Different contexts call for different integration strategies. These four patterns cover the most common use cases — from maximum simplicity to maximum control.

Full identity prefix

Paste the entire exported markdown at the top of your system prompt. Best for general-purpose assistants where you want full context.

ChatGPT custom instructions, Claude Projects, Gemini Gems

Code DNA only

Export only the Code DNA layer and paste into coding assistant system prompts. Keeps tokens low while giving the AI your full technical profile.

Cursor system prompt, Cline .clinerules, GitHub Copilot instructions

Layer-by-layer injection

Some systems (like Claude Projects) support multiple knowledge documents. Split your export by layer and upload each as a separate document.

Claude Projects with multiple knowledge files

Template variable substitution

Use the template format to build a custom system prompt where only specific fields are substituted. Gives you full control over the prompt structure.

Custom pipelines, LangChain prompts, fine-tuned workflows

Next steps

Automate beyond copy-paste

Ready to export?

Complete your interview, then find your export in the dashboard under Distribution → Markdown.