written by ForgeCat

Continual Learning

Incrementally keep AGENTS.md current from transcript changes.

Tags

• Agent Memory
• Automation
• Transcripts
• Cursor

Installation

npx forgecat install @forgecat/cursor_plugins_continual-learning

Skills

• continual-learning — Orchestrate continual learning by delegating transcript mining and AGENTS.md updates to agents-memory-updater.

Agents

• agents-memory-updater — Mine high-signal transcript deltas, update AGENTS.md, and keep the incremental transcript index in sync.

Details

Compatibility

Platforms

Dependencies

• Bun is required for the Cursor Stop hook.

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written by original source

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 orchestrates the learning flow.
• An agents-memory-updater subagent that mines new or changed transcripts and updates AGENTS.md.

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

/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 skill is marked disable-model-invocation: true, so it will not be auto-selected during normal model invocation. When it does run, it delegates the full memory update flow to agents-memory-updater.

The hook keeps local runtime state in:

• .cursor/hooks/state/continual-learning.json (cadence state)

The updater 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 memory updater writes only:

• ## Learned User Preferences
• ## Learned Workspace Facts

Each item is a plain bullet point.

License

MIT