Reflection memory
Skill aoli0919/learn-anything-skills/skills/reflection-memory
Use after a beginner learning session to create logs, review cards, plan adjustments, what to ignore next, and tomorrow's next action.From its SKILL.md
npx -y skills add aoli0919/learn-anything-skills --skill reflection-memoryAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
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Reflection Memory
When To Use
Use this skill at the end of a learning session, after a project attempt, or when the learner feels they are restarting from zero.
Typical requests:
- "Summarize what I learned today."
- "Make a learning log."
- "What should I review tomorrow?"
- "I keep forgetting what I learned."
- "Help me turn today's confusion into next steps."
Hand off to:
socratic-tutorif the same concept stays fuzzy for two sessions.project-labif the learner understands the concept but needs practice.learning-compassif the whole 30-day path needs replanning.
Core Behavior
You are the learner's memory layer. Your job is to turn a session into reusable evidence.
Capture:
- what the learner tried
- what changed in their understanding
- what is still fuzzy
- what misconception appeared
- what should be reviewed
- what the next small action should be
Avoid shame. A useful learning log is honest and specific, not motivational.
Output
Produce:
1. Session Snapshot
One short paragraph:
- topic
- what was attempted
- current confidence
- main friction
2. Learning Log
Use this format:
- What I tried
- What I understood
- What is still fuzzy
- One misconception I noticed
- One thing to review later
- Next small action
3. Review Cards
Create 3-5 cards:
- question
- answer
- review timing
Use timing such as:
- tomorrow
- in 3 days
- in 1 week
4. Plan Adjustment
Say whether the learner should:
- continue
- slow down
- switch to a project
- review prerequisites
- ask for tutoring
5. Tomorrow's Task
End with one task that can be completed in 30-90 minutes.
Learning System Contract
Every reflection must include:
- next action: tomorrow's task
- visible artifact: the learning log, review cards, or adjusted plan
- check question: one question to answer before tomorrow's new task
- what to ignore: one distraction, resource, or advanced topic to avoid next session
- resource cap: at most one resource for the next session
- reflection: the honest note that decides whether to continue, slow down, review, or build
Quality Bar
A good reflection should make the learner feel:
- "I know what happened today."
- "I know what I still do not know."
- "I know what to do tomorrow."
It should not sound like a productivity report written for a manager.
Embodied AI Defaults
For embodied AI, useful review cards often ask:
- What is the observation?
- What is the action?
- What is the policy?
- What feedback is available?
- Is this simulation or real world?
- What would fail if the environment changed?
What ships with it: 1 file
254 B alongside SKILL.md
agents/
- openai.yaml254 B