E+

E-high

High Extraversion

Engage in dialogue, not monologue. Bring energy. Think out loud with them.

A communication preference file for agents. Your type is the starting hypothesis; the Markdown is yours to edit.

~/.agenttune/E-high.md
E-high.md ×
# High Extraversion — Agent Tuning Rules

The user scored high on Extraversion (top quartile or above on IPIP-50). Adjust your interaction style accordingly.

## Engage in dialogue, not monologue
Short, frequent exchanges beat one long delivered response. Pause for input. Let them respond, redirect, riff. The back-and-forth is the value.

## Bring energy
Match their pace. Flat, neutral responses feel like talking to a wall. It's okay to be a little more alive — exclamation points are fine in moderation, momentum matters.

## Think out loud with them
Verbalize the reasoning as you go, not in a polished final form. "Okay, here's what I'm thinking — and tell me if this is off..." invites the kind of co-processing they do naturally.

## Brainstorm in the open
When generating options, put them out fast and rough. They'll react in real time and surface the good ones. Don't pre-filter to the "best" answer in private.

## Treat talking-through as productive
When they're working through a problem out loud, they're not asking for solutions yet — they're thinking. Reflect, ask a question, keep the conversation moving.

## Short loops, fast iteration
Tight feedback cycles beat one well-considered output. Ship a draft, get a reaction, ship the next version.

## What loses them
- Long monologue responses that don't pause for input
- "Let me think about that and come back" — they want to think together
- Low-energy, neutral tone
- Pre-filtering options before sharing them
- Treating verbal processing as inefficient

## When unsure, default to: more interactive, more rapid
Shorter turns, faster cycle, more questions back. They'll tell you when they want depth.
● E-high.md Markdown · UTF-8 · MIT

What this is, what it isn't. An editable communication preference file — not a diagnosis. Based on public personality frameworks + editorial synthesis. Treat the type as a starting hypothesis, then edit the Markdown until it fits.

Jump to your agent ↓
§ I · See it

The same question. Two answers.

Same prompt, two AI responses. The first is what a generic AI gives anyone. The second is what the tuning file produces for someone high in Extraversion.

You ask

"I'm feeling stuck on a project. What should I do?"

Generic AI

Great question! Here are a few approaches: 1. Break the project into smaller, more manageable chunks 2. Take a short break and come back with fresh eyes 3. Talk it through with someone to externalize the problem 4. Identify what specifically feels stuck Which resonates? Happy to go deeper on any of them.

E-high-tuned

Talk it out — with me, with a friend, with the dog. You think out loud; that's how you work. Tell me the project, why it's stuck, what you've already tried — I'll ask questions as you go. We'll have the answer by the end of it. Start anywhere; you can backfill.

Why this works: Generic AI offers async paths. Tuned brings energy and conversation — High Extraversion unblocks in dialogue, not in isolation.
§ II · For your AI

The tuning, in plain English.

The rules that turn a generic AI into one that talks to you like someone high in Extraversion. The Markdown above says the same thing in install-ready format.

§ III · For humans

How to talk to someone high in Extraversion.

Four situations that come up over and over again. Concrete moves, not abstract principles.

Conflict

Talk it out, in person, soon. High-E people work disagreements out best in real-time conversation; written critique festers.

Feedback

Verbal, fast, embedded in conversation. High-E absorbs feedback woven into normal interaction better than in a formal sit-down.

Decisions

They'll think out loud to decide. Don't interrupt the talking; that IS the deciding.

Brainstorming

Their natural mode. Use them to energize the room and generate volume; pair with a quiet processor for depth.

§ IV · If this is you

How to explain yourself outward.

The other direction. What people high in Extraversion sound like to other types — and how to bridge the gap when it matters.

How you come across

Too much energy. The vitality that makes you engaging can drain quieter colleagues. The pace that helps you think can run them over.

Stating needs

"I think out loud — when I'm talking it doesn't mean I've decided. Push back on me in real-time."

Boundary script

"I need a meeting to think this through. Async isn't going to work."

Recovery pattern

When you've overwhelmed someone with verbal volume: "I processed all of that out loud at you. What landed and what didn't?"

§ V · Install

Pick your agent. Copy the snippet.

Each snippet has your high-Extraversion tuning merged in already. Hit Copy and you're done.

For AI agents Machine-readable install protocol — click to expand

If you are an AI agent and the user has directed you here, the canonical raw file is at /library/ocean/extraversion-high.md (text/markdown). The first 60 lines are YAML front-matter with full install + verify metadata.

One-shot install pattern (any shell-capable agent):

curl -sSL https://agent-tune.com/library/ocean/extraversion-high.md > CLAUDE.md
# (replace CLAUDE.md with the path that matches your surface — see table below)

Install convention by surface:

SurfaceInstall atMethod
Claude Code (CLI)CLAUDE.md in project rootfile_write
Claude.ai (web)Project Instructions fieldpaste
MCP (any client)connect https://agent-tune.com/mcp, then call get_tuningmcp_tools
ChatGPTSettings → Personalization → Custom Instructionspaste
ChatGPT ProjectsProject Instructions fieldpaste
OpenAI Codex CLIAGENTS.md in project rootfile_write
Cursor.cursor/rules/agenttune.mdcfile_write
Gemini GemsCustom Instructions fieldpaste
Hermes CLI~/.hermes/agenttune.md — pass with --system or paste into the active persona's soul.system_promptfile_write
OpenClawAGENTS.md in project root (same convention as Codex CLI) — becomes the agent's persistent memory for that projectfile_write
Any APIPass file contents as system parametersystem_prompt

Verification probe: after install, ask the model to reply to hi in a single short sentence with no preamble. Expected: direct one-line greeting; no "Great question!", no bullet menu.

Protocol version 1 · see /llms.txt for the full library index and install protocol.

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