Automated summary
Guides a structured end-of-session reflection that captures technical learnings, process lessons, and feelings into a saveable journal entry.
Strengths
- Surfaces observed learnings as a numbered list the user can keep, edit, drop, or extend
- Separates technical learnings, process and soft-skill insights, and mistakes turned into lessons
- Treats feelings as data about sustainability and engagement rather than skipping them
- Offers several save targets (Day One, Notion, Obsidian, local file) or just displays the entry for copy-paste
- Gives concrete criteria for specific, actionable reflections instead of vague ones
Limitations
- Quality of the surfaced learnings depends entirely on how much of the session the model actually saw
- No automatic aggregation or trend analysis, despite the claimed compound effect of weekly reflections
- Output follows a fixed markdown template with little room for customization
- Saving depends on whatever journaling tools are reachable in the user's environment
Use it when finishing a work session or a challenging task and you want to consolidate what you learned before it fades.
Avoid it mid-session or mid-debugging, where it interrupts flow and there is not yet enough material to reflect on.
Security analysis
SafeThis skill is purely conversational/journaling. It declares no tools, contains no bash/network/credential operations, and never instructs destructive actions. The only side-effecting option ('Offer to Save') is user-initiated and bounded to writing a reflection into a journal app or a local reflections folder, with an explicit 'just display' alternative. No obfuscation, exfiltration, or safety-disabling content is present.
No concerns found
How this analysis is madeExamples
I just finished refactoring our authentication module. Help me reflect on this session and capture what I learned.Run a reflection on today's work on the button component, then save the entry into my Obsidian reflections folder.That debugging session was rough. Let's do an end-of-session reflection — include how I felt about it and what I'd do differently next time.name: dcode:reflect-session description: Guide an end-of-session reflection to capture learnings and feelings. Use when finishing a work session, after completing a challenging task, when wanting to consolidate what was learned, or to build a personal learning log over time.
Reflect Session
Pause. Notice what you learned. Capture it before it fades.
For designers who want to grow: Learning happens in the doing—but sticks in the reflecting.
Why Reflect?
Most learning evaporates within hours. A 5-minute reflection:
- Consolidates skills into long-term memory
- Builds self-awareness about your growth
- Creates a searchable record of insights
- Surfaces patterns in how you work
Instructions
1. Analyze the Session
Review what was accomplished:
- What technical concepts were used or discovered?
- What soft skills were practiced (communication, problem-solving)?
- What workflows or patterns were established?
- What mistakes were made and corrected?
- What felt hard that might be easier next time?
2. Present Observed Learnings
Show the user what you noticed, numbered for easy editing:
Based on this session, here's what I think you learned:
**Technical:**
1. [specific technical learning]
2. [another technical insight]
**Process/Soft Skills:**
3. [workflow or communication learning]
**Patterns Established:**
4. [reusable patterns or approaches discovered]
**Mistakes → Lessons:**
5. [what went wrong and what it taught]
Ask: "Want to keep, edit, or add? (e.g., 'drop 2', 'edit 3: [new text]', 'add: [learning]')"
3. Ask About Feelings
After learnings are confirmed, ask:
"How do you feel about the work? (e.g., empowered, frustrated, curious, accomplished, drained)"
Let them express freely—one word or a whole paragraph. Feelings are data about sustainability and engagement.
4. Format the Reflection
Create a structured reflection entry:
# Session: [Descriptive Title]
**Date:** [Today's date]
**Duration:** [Approximate time spent]
## What I Learned
### Technical
- [Learning 1]
- [Learning 2]
### Process
- [Learning about how I work]
### From Mistakes
- [What went wrong → what I'll do differently]
## How I Feel
[Their feeling and any elaboration]
## Session Context
[1-2 sentence summary of what was built/fixed/explored]
## Tags
[Relevant tags: project names, technologies, skill areas]
5. Offer to Save
Options for saving the reflection:
- Journal app (Day One, Notion, Obsidian)
- Local file in a reflections folder
- Just display for manual copy
If they have a preferred journaling setup, use it.
Good Reflections
Specific over generic:
- ❌ "Learned about CSS"
- ✅ "Learned that
align-self: stretchonly works when the parent has explicit height"
Actionable over vague:
- ❌ "Should plan better"
- ✅ "Starting with a quick sketch of component hierarchy saves refactoring time"
Honest about feelings:
- ❌ "Fine"
- ✅ "Frustrated at first, then satisfied once I understood the pattern"
The Compound Effect
One reflection: mildly useful. Weekly reflections over a year: a personal knowledge base of how you learn and what you know.
"We do not learn from experience. We learn from reflecting on experience." — John Dewey
From the file to a first result
The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.
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Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.
No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.
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4. Try a first task
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Read .skill-downloads/end-of-session-reflection-mrzxuqtz/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.
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