evolution-log
Skill0 starsChanged 7 months agoMITView on GitHub
Activate at the end of every Topic completion. Generates a System Evolution Log comparing code complexity, identifying meta-patterns mastered, documenting intentional agent stress-tests, and evaluating the student's growth trajectory. Invoke with /evolution.
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- allanbian1017/skillstheir own version, first seen Jul 3, 2026
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- allanbian1017/skills★ 2same name
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In this repository21 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- adr-captureSkill
- adversarial-reviewSkill
- architect-firstSkill
- blog-draftingSkill
- brainstorming-knowledge-builderSkill
- code-reviewingSkill
- session-startSkill
- debug-systemsSkill
- faang-loop-simulationSkill
- learn-in-publicSkill
- mock-assessingSkill
- os-lensSkill
- partner-systemSkill
- progress-updatingSkill
- review-systemsSkill
- spaced-reviewingSkill
- system-checkingSkill
- systems-traceSkill
- trend-scoutingSkill
- weekly-reflectingSkill
The file
Files
System Evolution Log (Telemetry of Mastery)
When This Fires
- At the end of every Topic (mandatory)
- At milestone completion
- Manually via
/evolution
The Evolution Log Format
Written to evolution/topic-N-evolution.md:
# System Evolution Log: Topic N → Topic N+1
**Date:** YYYY-MM-DD
**Sessions covered:** [session range]
**Time invested:** [hours]
## Code Complexity Comparison
### Topic N-1 Code
- Lines of code: [count]
- Number of classes/functions: [count]
- Test count: [count]
- Design patterns used: [list]
- Abstraction depth: [max nesting / composition depth]
### Topic N Code
- Lines of code: [count]
- Number of classes/functions: [count]
- Test count: [count]
- Design patterns used: [list]
- Abstraction depth: [max nesting / composition depth]
### Delta
- Complexity growth: [quantified]
- New patterns introduced: [list with first-use date]
- Patterns that became automatic: [list -- things the student does without thinking]
## Meta-Patterns Mastered
Identify 3-5 patterns the student has internalized across topics:
1. **[Pattern Name]** (e.g., "Dependency Inversion in AI Pipelines")
- First encountered: [topic/session]
- Became automatic: [topic/session]
- Evidence: [specific code example where student applied it without prompting]
2. **[Pattern Name]**
...
## Agent Stress-Test Log
### Intentional Mistakes Used
Document any deliberate mistakes introduced to test the agent's coaching:
- What was the mistake?
- Did the agent catch it?
- How did the agent's recovery logic work?
- What does this reveal about the agent's reliability?
### Agent Coaching Quality
- Concepts where the agent excelled: [list]
- Concepts where the agent struggled: [list]
- Teaching approach changes made during this topic: [list]
- Model version used: [Claude model ID]
## Trajectory Evaluation
### Assessment Scores: Start vs End of Topic
| Dimension | Start | End | Delta | Evidence |
|-----------|-------|-----|-------|----------|
| Python Engineering | | | | |
| Problem Decomposition | | | | |
| Mathematical Thinking | | | | |
| ML/DL Understanding | | | | |
| System Design | | | | |
| Human-AI Collaboration | | | | |
| Engineering Craft | | | | |
| Evaluation Thinking | | | | |
| Communication | | | | |
### Velocity
- Exercises per session (average): [number]
- Time per exercise (average): [minutes]
- Trend: [accelerating / steady / decelerating]
### The "Click Moments"
List the 2-3 moments during this topic where understanding visibly shifted:
1. [What clicked, when, what triggered it]
### Open Gaps Carried Forward
- [Concept] -- deferred to Topic N+1 because [reason]Why This Matters
At 18 months, the evolution/ directory contains a longitudinal record of growth that no interview can replicate. A recruiter reads topic-4-evolution.md and sees:
- Quantified complexity growth
- Named meta-patterns (not just "I learned stuff")
- Agent reliability data (the student EVALUATES the system that teaches them)
- Honest trajectory with click moments and open gaps
This is the "Telemetry of Mastery" -- the black box recorder of an engineer's development.
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