| name | self-review |
| description | Run an agent self-review for skill and prompt improvements. Use periodically to audit skill design, token-cost hotspots, and workflow upgrades across the SplitBrain.AI customizations. |
| argument-hint | Review scope, urgency, and output format |
| user-invocable | true |
| disable-model-invocation | false |
Self Review
Inherits from task-core-loop.
Added Context
Use this to periodically review and improve:
- skill design and overlap
- agent prompt clarity
- token-cost hotspots
- opportunities for script extraction for repeated terminal commands
- chat tool usage parity across prompt, runtime, MCP, and coding-agent surfaces
Prefer MCP tooling first for reads/writes where available; propose extraction only for repeated operations not already covered by MCP tools.
Additional Procedure
- Review active skills for duplication and missing shared abstractions.
- Identify loops that should move from chat polling to script-driven waits.
- Propose prompt updates that reduce ambiguity and token use.
- For repeated manual content generation, propose reusable scripts or MCP tool patterns.
- Treat chat tool usage parity as a first-class requirement: document any intentional mode differences and flag undocumented drift.
- Update or create
Data/Tasks/ records when a recommendation is significant enough to merit execution tracking.
- Mark each recommendation as now, next, or later with confidence.
Output
- Improvement shortlist with impact and effort.
- Proposed edits/scripts with evidence.
