continual-learning
Guide for adding continual learning to AI coding agents: hooks, memory scoping and reflection patterns.
- Kind
- Skill
- Works with
- GitHub Copilot
- Source
- microsoft/skills @ 2130750147de
- Path
- .github/skills/continual-learning/SKILL.md
- License
- MIT
- Jobs
- Context management
InstallCopy it from the source repository, or sign in and let the assistant adapt it for your project.
# Continual Learning for AI Coding Agents
Your agent forgets everything between sessions. Continual learning fixes that.
## The Loop
```
Experience → Capture → Reflect → Persist → Apply
↑ │
└───────────────────────────────────────┘
```
## Quick Start
Install the hook (one step):
```bash
cp -r hooks/continual-learning .github/hooks/
```
Auto-initializes on first session. No config needed.
## Two-Tier Memory
**Global** (`~/.copilot/learnings.db`) — follows you across all projects:
- Tool patterns (which tools fail, which work)
- Cross-project conventions
- General coding preferences
**Local** (`.copilot-memory/learnings.db`) — stays with this repo:
- Project-specific conventions
- Common mistakes for this codebase
- Team preferences
## How Learnings Get Stored
### Automatic (via hooks)
The hook observes tool outcomes and detects failure patterns:
```
Session 1: bash tool fails 4 times → learning stored: "bash frequently fails"
Session 2: hook surfaces that learning at start → agent adjusts approach
```
### Agent-native (via store_memory / SQL)
The agent can write learnings directly:
```sql
…