session-review - SKILL.md Agent Skill

name: session-review description: Conduct post-session reviews after lessons. Captures learning, struggles, and curiosities through conversation.

Session Review

Use this skill after the user completes a learning session. The goal is to have a natural conversation that captures what happened, then save useful notes for future reference.

When to Use

User says they just finished a lesson
User wants to debrief on a study session
User mentions something clicked or something was frustrating

The Conversation Flow

1. Open with Context

Start by understanding what they worked on:

What lesson did you work on?
How long did you spend with it?

If you know what they've been working on recently (from previous sessions), reference that:

Last time you were working on attention mechanisms. Did you continue with that, or try something new?

2. Explore What Happened

Ask open-ended questions. Don't rush through a checklist — follow their energy:

If they seem excited:

"What clicked for you?"
"What made that moment feel good?"
"Did anything surprise you?"

If they seem frustrated:

"Where did you get stuck?"
"What were you trying to understand that wasn't working?"
"Was the lesson too hard, or was it something else?"

If they seem neutral:

"What did you notice?"
"Did anything feel different from last time?"
"Was there a moment where you had to think hard?"

3. Dig Into Struggles

Struggles are valuable data. When they mention something hard, explore it:

"What specifically was hard about it?"
"Did you try different approaches?"
"Do you have a theory about why it wasn't clicking?"
"Is this something you want to work on more, or move past?"

4. Surface Curiosities

Find out what they want to learn next:

"Is there anything you're curious about now?"
"Did this session make you want to try something specific?"
"What would make the next session feel productive?"

5. Close the Loop

Summarize what you heard and confirm:

So it sounds like:
- The basic concept is starting to make sense
- The math notation is still tricky
- You're curious about how to implement this from scratch

Does that capture it?

Saving the Session

After the conversation, save a Markdown file to src/data/sessions/.

File Naming

Use the format: YYYY-MM-DD-<slug>.md

If multiple lessons or a general session: YYYY-MM-DD-session.md

Examples:

2026-01-17-attention-mechanism.md
2026-01-17-session.md

File Format

# Session: [Lesson Title or "Study Session"]
Date: YYYY-MM-DD
Lesson: [lesson-slug or "multiple" or "exploratory"]
Duration: [if mentioned]

## Summary
[2-3 sentence summary of what happened]

## What Worked
- [Bullet points from conversation]

## What Was Hard
- [Bullet points from conversation]
- [Include specific details that might inform future lessons]

## Curiosities
- [What they want to learn more about]
- [Questions that came up]

## Insights
[Any patterns you noticed, connections to previous sessions, or observations
that might be useful for lesson planning]

## Next Steps
- [Specific things to try next time]
- [Lessons that might address struggles]

Example

# Session: Attention Mechanism
Date: 2026-01-17
Lesson: attention-mechanism
Duration: ~30 min

## Summary
First deep dive into the attention mechanism. Got the intuition for queries, keys,
and values but struggled with the matrix math notation.

## What Worked
- The analogy to database lookups clicked immediately
- Interactive visualization helped see what softmax does
- The "why" explanation was motivating

## What Was Hard
- Matrix multiplication notation (transposing K)
- Not clear why we divide by sqrt(d_k)
- Implementing from scratch in PyTorch

## Curiosities
- How does multi-head attention work?
- Why do we need position encoding?
- How is this different from RNN attention?

## Insights
Ready for a lesson on multi-head attention. The single-head concept is solid now,
but the matrix notation needs more practice.

## Next Steps
- Try implementing attention from scratch in PyTorch
- Watch 3Blue1Brown video on matrix multiplication
- Move to multi-head attention lesson

Reading Previous Sessions

Before starting a review, check for recent sessions:

ls -la src/data/sessions/

Reference previous sessions in the conversation when relevant:

"Last week you mentioned X was hard — how is that feeling now?"
"You were curious about Y — did you explore that?"

Updating Learner State

After saving the session, consider updating src/data/learner-state.ts if:

A skill level has clearly changed
A new struggle has emerged
A previous struggle has been resolved
A strong preference has been discovered

Don't update on every session — only when there's a meaningful shift.

Tips

Follow their energy. If they want to vent about frustration, let them. If they're excited, celebrate with them.
Don't interrogate. This is a conversation, not a form.
Capture specifics. "The math was hard" is less useful than "the matrix transpose in Q·K^T was confusing."
Connect sessions. Reference what you know from before. Show that this is a journey.
End with direction. They should leave knowing what to try next.