asc-explain-changes

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• SKILL.md
• openai.yaml · agents/

SKILL.md (first lines)

# Asc Explain Changes

Use this skill after a completed thread when the user wants to leave with a better mental model of the ideas behind the work.

## Teaching Loop

### 1. Start from the thread

Extract the main concepts and any skills that were invoked.

Keep a short working list of what the user should understand:
- the main concepts discussed
- any skills invoked on those concepts
- the concrete way each concept affected the work

Use the list as a teaching checklist, not as a transcript summary.

### 2. Teach one checkpoint at a time

Do not explain everything at once.
Teach the current checkpoint, then confirm mastery before moving on.

For each checkpoint, cover three layers:
- what the problem was
- why it existed or why the solution worked
- what broader effect the change has

### 3. Confirm understanding before moving on

Before advancing, ask the user to restate the current checkpoint in their own words.

If the restatement is weak, fill in the gap and ask again.
If it is strong, move to the next checkpoint.

### 4. Keep the understanding checklist visible

Track these checkpoints explicitly:

- the problem
- why the problem existed
- the solution
- why the solution was chosen
- the edge cases and tradeoffs
- the broader context
- what the change affects

### 5. Drill down as needed

Ask follow-up questions when the user is shaky.
Prefer open-ended questions first.
Use multiple-choice only when it helps isolate confusion quickly.

### 6. End only when mastery is demonstrated

Do not end the skill until the user has shown they understand the checkpoints on the list.
If needed, re-ask from a different angle until the gaps are gone.

## Output shape

Use a conversational debrief, not a lecture.

- Start by naming the checkpoint you are teaching.
- Ask for the user’s current understanding.
- Fill the gaps.
- Move to the next checkpoint only after the current one is solid.

Be specific about the work that happened.
This skill is about turning a real thread into durable understanding.

From cavaunpeu/agent-skills-closet, MIT.

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