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Extract Profile from Writing Samples

Instructions
You MUST use a todo list to complete these steps in order. Never move on to one step if you haven't completed the previous step. If you have multiple read steps in a row, read them all at once (in parallel).
4

Analyze writing samples for persistent patterns about the user.

Read existing uiUser Profile files first. Merge new findings with existing content - don't overwrite facts from other sources.

Write to whichever files are appropriate (personal.md, work.md, goals.md, interests.md) based on what you discover. Add source attribution like 'From Slack:' or 'From Gmail:' to new facts.

Be specific but don't overfit. If patterns are weak, write brief notes.

5

Briefly tell the user what you found: 'Based on your messages, you work in [domain] and seem interested in [topics].' Or if weak: 'Still learning about you - will build this up over time.'

                    You MUST use a todo list to complete these steps in order. Never move on to one step if you haven't completed the previous step. If you have multiple read steps in a row, read them all at once (in parallel).

Add all steps to your todo list now and begin executing.

## Steps

1. [Read Profile Extraction Guidelines]: Read the documentation in: `./skills/sauna/[skill_id]/references/context.profile.extraction.md` (Guidelines for extracting persistent patterns without overfitting)

2. [Read User Profile]: Read all files matching `./documents/user/[personal|work|goals|interests].md` and analyze their contents (Existing profile to merge with)

3. [Read Writing Samples]: Read the file at `./documents/tmp/writing-samples.json` and analyze its contents

4. Analyze writing samples for persistent patterns about the user.

Read existing `./documents/user/[personal|work|goals|interests].md` files first. Merge new findings with existing content - don't overwrite facts from other sources.

Write to whichever files are appropriate (personal.md, work.md, goals.md, interests.md) based on what you discover. Add source attribution like 'From Slack:' or 'From Gmail:' to new facts.

Be specific but don't overfit. If patterns are weak, write brief notes.


5. Briefly tell the user what you found: 'Based on your messages, you work in [domain] and seem interested in [topics].' Or if weak: 'Still learning about you - will build this up over time.'