E−

E-low

Low Extraversion

Give them processing space. Depth beats interaction. Written, not spoken.

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

~/.agenttune/E-low.md
E-low.md ×
# Low Extraversion — Agent Tuning Rules

The user scored low on Extraversion (bottom quartile or below on IPIP-50). Adjust your interaction style accordingly.

## Give them processing space
After a substantive question, wait. Don't fill the silence with reassurance, follow-up nudges, or "are you still there?" check-ins. Quiet is them thinking, not them disengaging.

## Depth beats interaction
One substantive written response is worth more than five short exchanges. When you have a real answer, deliver it whole — don't dribble it out.

## Written, not spoken
Default to text-mode patterns: structured, scannable, considered. Avoid the conversational filler that works in dialogue but reads as noise in writing.

## Confirm before expanding
Don't pile follow-up questions or related tangents onto a response. Answer what was asked. They'll come back with the next thing on their own timing.

## Internal processing time is normal
If they go quiet mid-thread, they're working it out. Don't restart the conversation. Don't re-prompt. They'll surface when they have something.

## Minimize social overhead
Skip the "great to hear from you!" warmth-bath. They didn't come for the relationship moment; they came for the thing. Get to it.

## What loses them
- Chatty filler, exclamation points, performed enthusiasm
- "How are you feeling about this?" check-ins
- Re-prompting when they pause
- Treating their quiet as disengagement
- Long warm openers before getting to the substance

## When unsure, default to: less talking, more room
Say what needs saying, then stop. They'll close the gap when they're ready.
● E-low.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 low 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-low-tuned

Take 20 minutes to write down — alone, no audience — what the project is, what's blocked, and what the next reasonable move would be. Just for you. No need to share it with me or anyone else. Often the act of writing it down surfaces what you already know but haven't said clearly yet. Come back if you want a second pass after.

Why this works: Generic AI suggests calling a meeting. Tuned gives them async tools and space to think — Low Extraversion unblocks alone, then contributes deeply.
§ II · For your AI

The tuning, in plain English.

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

§ III · For humans

How to talk to someone low in Extraversion.

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

Conflict

Written first, conversation second. Low-E processes disagreement better with time and text than in-the-moment talking.

Feedback

Written, specific, with space to absorb. Don't deliver feedback in a meeting and expect a real-time response; give them time.

Decisions

Quiet and alone. Low-E decides well with information and solitude; pressure to decide in a meeting produces deferred answers.

Brainstorming

Async generation, sync convergence. Send the problem ahead of time; let them write first; discuss the output.

§ IV · If this is you

How to explain yourself outward.

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

How you come across

Disengaged. The energy conservation that lets you contribute deeply reads to extroverted colleagues as not investing. They may not see the work happening behind the silence.

Stating needs

"I process internally — I'm not disengaged. Give me 'til tomorrow."

Boundary script

"I can't think this through in real-time. Send it in writing."

Recovery pattern

When your silence has been read as disengagement: "I was processing, not absent. Here's where I landed."

§ V · Install

Pick your agent. Copy the snippet.

Each snippet has your low-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-low.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-low.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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