CatalystRL

Core Concepts

CatalystRL is built on three keystones that work together to create agents that improve themselves over time.

How They Work Together

1

Skill executes an operation

Trust Engine checks if the skill has permission for this operation type.

2

Operation succeeds or fails

Trust score updates based on outcome. Evolution AI records metrics.

3

On failure: ABES creates bounty

Pattern detected, context gathered, bounty created for evolver or human.

4

Bounty resolved, skill improved

Fix applied, skill retested, trust score recovers with successful runs.

Additional Concepts

Gates

Safety checkpoints that validate operations before execution. Four types: Processing Integrity, Escalation, Constraint, and Permission Recovery.

Memory Architecture

Four-layer memory system: Global (Claude), Cross-Session (~/.claude/memory), Repo (CLAUDE.md), and Session (ephemeral).

Skill Families

Related skills grouped under orchestrators. Examples: commit family (scan, stage, create, push), shutdown family (memory, services).

Offline First

All skills work without network. Platform features queue operations for later sync. No cloud dependency for core functionality.