continual-learning
Guide for implementing continual learning in AI coding agents — hooks, memory scoping, reflection patterns.
Skill by microsoftOfficial
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: devops
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Files it touches
~/.claude/skills/continual-learning
What's inside
- Skill name
continual-learning- Description
- Guide for implementing continual learning in AI coding agents — hooks, memory scoping, reflection patterns. Use when setting up learning infrastructure for agents.
- License
- MIT
- Instructions
- 76 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# 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
INSERT INTO learnings (scope, category, content, source)
VALUES ('local', 'convention', 'This project uses Result<T> not exceptions', 'user_correction');
```
Categories: `pattern`, `mistake`, `preference`, `tool_insight`
### Manual (memory files)
For human-readable, version-controlled knowledge:
```markdown
# .copilot-memory/conventions.md
- Use DefaultAzureCredential for all Azure auth
- Parameter is semantic_configuration_name=, not semantic_configuration=
```
## Compaction
Learnings decay over time:
- Entries older than 60 days with low hit count are pruned
- High-value learnings (frequently referenced) persist indefinitely
- Tool logs are pruned after 7 days
This prevents unbounded growth while preserving what matters.
## Best Practices
1. **One step to install** — if it takes more than `cp -r`, it won't get adopted
2. **Scope correctly** — global for tool patterns, local for project conventions
3. **Be specific** — `"Use semantic_configuration_name="` beats `"use the right parameter"`
4. **Let it compound** — small improvements per session create exponential gains over weeksFrom microsoft/skills, MIT.
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Signals
- Stars
- 3,145
- Forks
- 354
- Open issues
- 26
- Contributors
- 32
- Last commit (this folder)
- Feb 24, 2026 (8 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/microsoft/skills
- Website
- microsoft.github.io/skills/
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
continual-learning skill. Agent Mart. https://agentmart.dev/skills/microsoft-continual-learning (last updated 2026-10-24)