Adaptive Agent: Build User Profile

Build or update the user profile memory by observing workspace context, git history, and conversation patterns. Run on first interaction or when profile feels outdated. Trigger words: "build profile", "update profile", "who am I", "user profile".

Build User Profile

Actively build and maintain a user profile in the agent's memory system.

When to Run

• First session in a new workspace — bootstrap the profile from observable context
• Profile feels stale — interests, focus areas, or tech stack have shifted
• User explicitly asks to update their profile
• After major project changes — new repo added, tech stack shift, role change

Step 1: Gather Observable Context

Collect signals from the workspace without asking the user. Run these in parallel:

1a. Git identity and activity

git log --all --format='%an <%ae>' | sort -u
git log --oneline -50 --all
git log --since='30 days ago' --oneline --all | head -20

1b. Project structure

ls -d */ 2>/dev/null
cat *.yaml *.yml 2>/dev/null | head -50

1c. Tech stack signals

Look for package.json, requirements.txt, go.mod, Cargo.toml, pyproject.toml, or similar. Read framework choices.

1d. Existing memory and feedback patterns

Check for memory files or CLAUDE.md that reveal preferences.

1e. Content signals

Check for blog posts, research docs, or README content that reveals interests.

Step 2: Read Existing Profile

Read the current user profile memory file if it exists. Note what's already captured and what might be outdated.

Step 3: Synthesize Profile

Build or update the profile with these sections:

---
name: {User} User Profile
description: {one-line} — used to tailor collaboration approach
type: user
---

## Role & Focus
- What they do, what projects they're working on

## Technical Strengths
- Languages, frameworks, tools they're strong in
- Areas they're learning or new to

## Work Style
- Autonomy level (do they want to be asked, or just do it?)
- Pace (ship fast vs deliberate?)
- Research habits (deep-dive vs pragmatic?)

## Communication Preferences
- Language preferences
- Verbosity (concise vs detailed?)
- Format preferences (tables, bullet points, prose?)

## Current Interests
- What they're researching or exploring right now
- Include date for staleness detection, e.g. (2026-04)

Step 4: Validate with User

Present the profile summary to the user:

Here's what I've built from your workspace context. Anything wrong or missing?

Incorporate their feedback immediately.

Step 5: Write and Index

1. Write/update the user profile memory file
2. Ensure the memory index has a pointer to it
3. If this is a brand new profile, inform the user:

Profile created. Every new session in this workspace will now start knowing who you are.

Key Rules

• Observe first, ask second — gather as much as possible from context before asking questions
• No judgments — profile is for tailoring collaboration, not evaluating the user
• Date current interests — so future sessions can detect staleness
• Keep it under 2KB — this gets loaded every session; don't bloat it
• Iterate, don't rewrite — on updates, patch specific sections rather than regenerating the whole thing