MANDATORY PREPARATION
Invoke /agent-workflow — it contains workflow principles, anti-patterns, and the Context Gathering Protocol. Follow the protocol before proceeding — if no workflow context exists yet, you MUST run /teach-maestro first.
Analyze the Maestro audit trail and decision log to produce a skill-effectiveness scorecard. This tells you which commands work, which fail, and where your workflow needs attention.
Data Sources
Read these files from the project root:
.maestro/audit.jsonl— every command invocation with duration, cost, and outcome.maestro/decisions.jsonl— decisions made with outcomes and next steps
If neither file exists, respond: *"No audit data found. Run commands with Maestro to start tracking, then come back."*
Analysis Dimensions
1. Usage Frequency
- Which commands run most/least?
- Are any commands never used? (candidates for removal)
2. Completion Rate
- What % of invocations complete successfully?
- Which commands fail most often?
3. Command Flow
- What are the most common command sequences (A → B)?
- Which commands lead to follow-ups vs. abandonment?
- Abandonment rate per command (no follow-up within 30 min)
4. Cost Distribution
- Total estimated cost across all commands
- Cost per command (average)
- Most/least expensive commands
5. Duration Analysis
- Average duration per command
- Outliers (unusually slow invocations)
Output Format
╔══════════════════════════════════════════╗
║ MAESTRO EFFECTIVENESS ║
╠══════════════════════════════════════════╣
║ Commands Run __ (__ unique) ║
║ Completion Rate __% ║
║ Most Used /_____ (__×) ║
║ Most Abandoned /_____ (__% ⚠️) ║
║ Avg Duration __s ║
║ Total Cost ~$__.__ ║
╠══════════════════════════════════════════╣
║ STRONGEST PIPELINES ║
╠══════════════════════════════════════════╣
║ /_____ → /_____ __× ║
║ /_____ → /_____ __× ║
╠══════════════════════════════════════════╣
║ COST PER COMMAND ║
╠══════════════════════════════════════════╣
║ /_____ $__.__/run ████░░ avg ║
║ /_____ $__.__/run █░░░░░ cheap ║
║ /_____ $__.__/run █████░ costly ║
╚══════════════════════════════════════════╝
INSIGHTS:
1. [Data-driven observation with recommended action]
2. [Data-driven observation with recommended action]
3. [Data-driven observation with recommended action]Insights Rules
Every insight MUST:
- Reference specific data (e.g., "40% abandonment rate")
- Suggest a specific Maestro command to address it
- Distinguish correlation from causation
Reflection Checklist
- All 5 analysis dimensions covered
- Scorecard generated with real data
- Insights are data-driven, not speculative
- Cost estimates labeled as approximate (~)
- Recommended actions reference specific Maestro commands
Recommended Next Step
After reflecting, run /streamline to remove unused commands, or /refine on the most-abandoned command to improve its prompt quality.
NEVER:
- Require audit data to exist — degrade gracefully
- Invent metrics beyond what the logs contain
- Show cost data without the "estimate" disclaimer (~)
- Make judgments without evidence (say "100% completion rate" not "works great")
- Compare across projects — reflect is project-scoped