// Use when a learned skill has low utility score, has been failing, or the user wants to improve an existing learned skill based on failure analysis
| name | memento-optimize |
| description | Use when a learned skill has low utility score, has been failing, or the user wants to improve an existing learned skill based on failure analysis |
Refine a learned skill based on failure analysis. Corresponds to the paper's skill-level reflective update.
If not specified by user, find candidates:
utility < utility_threshold AND usage_count >= min_samples_for_judgmentRead the target skill's trigger_log for failure entries. Also read the SKILL.md itself. Identify:
Make targeted edits:
Update the skill's metrics entry:
last_optimized: today's dateoptimization_count: increment by 1Do NOT reset usage/success/failure counts. The history is valuable.
Present a before/after diff of the SKILL.md changes to the user.
Use when memento-reflect identifies a reusable pattern worth capturing, or when the user explicitly wants to create a new learned skill from a task execution pattern
Use when the user wants to remove low-value learned skills, clean up unused skills, or reduce the learned skill library size
Use after completing any significant task to self-evaluate what worked or failed, update learned skill metrics, and discover reusable patterns worth capturing as new skills
Use when the user wants to see an overview of their learned skills, check utility scores, or identify skills that need optimization or pruning