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。
sharpdeveye/maestro5912026年4月29日 更新
免费在 GitHub 公开
refine
Use when the workflow works but needs polish, or as the final step in a diagnose → fix → refine cycle before shipping.
中文简介正在准备中。当前显示原文说明。
sharpdeveye/maestro星标 591(GitHub 591 + cccskills 0)
实测评分 未实测
查看安装方法包含的文件（1）
- SKILL.md2.9 KB
SKILL.md（原文）
安装前可以查看交给 AI 代理的指令内容。
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.
This is the final quality pass. The workflow works — now make it excellent.
Refinement Checklist
Prompts
- Every prompt follows the 4-zone pattern (role, context, instructions, output)
- Output schemas are explicit and validated
- Negative instructions clarify what NOT to do
- No contradictory instructions
- Few-shot examples included for ambiguous tasks
- Chain-of-thought used for multi-step reasoning tasks
Tool Descriptions
- Every tool has a multi-line description: what, when to use, when NOT to use, returns
- Input parameters have descriptions and types
- Error responses are documented
- At least one example input/output in the description
Error Messages
- Error messages are specific (not "an error occurred")
- Error messages suggest corrective action
- Errors include context (what was being attempted)
- Errors are structured (code + message + details)
Logging
- Every model call is logged (input tokens, output tokens, latency, cost)
- Tool calls are logged with inputs and outputs
- Errors are logged with full context
- PII is redacted from logs
- Workflow ID traces through all log entries
Configuration
- All magic numbers are named constants
- Environment-specific values are in config, not code
- Defaults are sensible — config is for overrides
- Cost ceilings are set
- Timeout values are set for all external calls
Output
For each checklist item that fails, provide:
- What's wrong (specific finding)
- Where it is (file, line, or component)
- How to fix it (concrete suggestion)
- Priority (critical / important / nice-to-have)
Priority Matrix
| Priority | Criteria | Maestro Action |
|---|---|---|
| Critical | Affects correctness or safety | /fortify or /guard before shipping |
| Important | Affects quality or maintainability | /calibrate in current cycle |
| Nice-to-have | Cosmetic or minor inconsistency | Note for next /refine pass |
Recommended Next Step
After refinement is complete, run /evaluate to verify the polished workflow against realistic scenarios.
NEVER:
- Skip the checklist — go through every item
- Mark items as passing without checking
- Suggest changes that alter behavior (this is polish, not redesign)
- Refine before the workflow is functionally correct (fix first, refine last)
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同一仓库的技能
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。
sharpdeveye/maestro5912026年4月29日 更新
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.
中文简介正在准备中。当前显示原文说明。
sharpdeveye/maestro5912026年4月29日 更新
amplify
免费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。
sharpdeveye/maestro5912026年4月29日 更新
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。
sharpdeveye/maestro5912026年4月29日 更新
capture
免费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。
sharpdeveye/maestro5912026年4月29日 更新