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# Continual Learning
Automatically and incrementally keeps `AGENTS.md` up to date from transcript changes.
The plugin combines:
- A `stop` hook that decides when to trigger learning.
- A `continual-learning` skill that mines only high-signal transcript deltas.
It is designed to avoid noisy rewrites by:
- Reading existing `AGENTS.md` first and updating matching bullets in place.
- Processing only new or changed transcript files.
- Writing plain bullet points only (no evidence/confidence metadata).
## Installation
```bash
/add-plugin continual-learning
```
## How it works
On eligible `stop` events, the hook may emit a `followup_message` that asks the agent to run the `continual-learning` skill.
The hook keeps local runtime state in:
- `.cursor/hooks/state/continual-learning.json` (cadence state)
The skill uses an incremental transcript index at:
- `.cursor/hooks/state/continual-learning-index.json`
## Trigger cadence
Default cadence:
- minimum 10 completed turns
- minimum 120 minutes since the last run
- transcript mtime must advance since the previous run
Trial mode defaults (enabled in this plugin hook config):
- minimum 3 completed turns
- minimum 15 minutes
- automatically expires after 24 hours, then falls back to default cadence
## Optional env overrides
- `CONTINUAL_LEARNING_MIN_TURNS` (or legacy `CONTINUOUS_LEARNING_MIN_TURNS`)
- `CONTINUAL_LEARNING_MIN_MINUTES` (or legacy `CONTINUOUS_LEARNING_MIN_MINUTES`)
- `CONTINUAL_LEARNING_TRIAL_MODE` (or legacy `CONTINUOUS_LEARNING_TRIAL_MODE`)
- `CONTINUAL_LEARNING_TRIAL_MIN_TURNS` (or legacy `CONTINUOUS_LEARNING_TRIAL_MIN_TURNS`)
- `CONTINUAL_LEARNING_TRIAL_MIN_MINUTES` (or legacy `CONTINUOUS_LEARNING_TRIAL_MIN_MINUTES`)
- `CONTINUAL_LEARNING_TRIAL_DURATION_MINUTES` (or legacy `CONTINUOUS_LEARNING_TRIAL_DURATION_MINUTES`)
## Output format in AGENTS.md
The skill writes only:
- `## Learned User Preferences`
- `## Learned Workspace Facts`
Each item is a plain bullet point.
## License
MIT