Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.
中文简介正在准备中。当前显示原文说明。
Capture a session summary — what was done, what decisions were made, and what to do next.
中文简介正在准备中。当前显示原文说明。
实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
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.
Capture the current session's work into a persistent summary. This creates a record that survives session boundaries — future commands can reference what happened here.
Read the conversation history and identify:
Generate a session summary file at .maestro/sessions/{date}_{topic}.md:
# Session: {topic}
Date: {YYYY-MM-DD}
## Commands Run
- /diagnose → Score: 18/25
- /fortify → Added retry logic to API handlers
- /evaluate → Verified with 3 test scenarios
## Decisions
- Chose retry-with-backoff over circuit breaker (simpler, sufficient for current load)
- Kept synchronous error handling (async not justified yet)
## Files Changed
- `src/api/handler.ts` — added retry wrapper
- `src/middleware/auth.ts` — added input validation
- `tests/api.test.ts` — new test file
## Open Issues
- Rate limiting not yet implemented (deferred to next session)
## Next Steps
1. Run `/guard` to add rate limiting
2. Run `/evaluate` with adversarial test cases
Also append a decision entry to .maestro/decisions.jsonl recording this capture.
.maestro/sessions/After capturing, your next session should start with /recap to restore context, then proceed with the next steps listed above.
NEVER:
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Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.
中文简介正在准备中。当前显示原文说明。
Use when porting a workflow to a different AI provider, deployment environment, model tier, or organizational context.
中文简介正在准备中。当前显示原文说明。
Use when any Maestro command is invoked — provides foundational workflow design principles across prompt engineering, context management, tool orchestration, agent architecture, feedback loops, knowledge systems, and guardrails.
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Use when the workflow works but needs to handle more complex cases or produce higher-quality output through better tools, context, prompts, or models.
中文简介正在准备中。当前显示原文说明。
Use when workflow components are inconsistent, naming conventions vary, or a new team member's work needs alignment to project standards.
中文简介正在准备中。当前显示原文说明。
Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.
中文简介正在准备中。当前显示原文说明。