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Retrospective Agent (Grade A)安全测试的数据ai技能,适用于Claude AI。级别A。每个轨道完成后运行以提取知识。分析了成功的、失败的和出现的模式。更新导演/知识/模式.md文件和错误.json文件

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Daniel Nikulshyn审阅者 Daniel Nikulshyn·更新 2026年7月

概览

Retrospective Agent 是为 Claude AI 设计的 data‑ai 技能。它在每个轨道完成后运行,提取学习点,分析哪些做得好、哪些失败以及出现了哪些模式。该技能会将新的解决方案更新到 conductor/knowledge/patterns.md 文件,并将新的错误模式写入 errors.json 文件。如果识别出工作流程改进,它还会提出技能更新建议。Retrospective Agent 在轨道达到 COMPLETE 状态后会自动触发。 该工具的工作流程包括分析轨迹执行数据,提取已完成工作的模式,检测错误模式,识别技能提升,并更新知识库。它会审阅轨迹的计划、执行摘要、任务、提交、规范和元数据。Retrospective Agent通过将新的模式添加到 patterns.md 文件以及新的错误模式添加到 errors.json 文件来更新知识库。 此技能在每次轨道完成后由编排器自动触发,为未来轨道提供持续学习体验。Retrospective Agent 通过提取可复用的解决方案、错误模式以及技能改进,帮助精炼该技能,可用于让未来轨道更加智能。

主要功能

  • 轨道执行分析
  • 模式提取和文档
  • 错误模式识别和解决
  • 技能改进建议
  • 知识库更新

价格

模型
Free
评分
暂无评价

使用场景

轨道后评估

在完成一个轨道后运行 Retrospective Agent 以提取知识并更新知识库.

工作流程优化

使用 Retrospective Agent 确定工作流程中的改进区域并提出技能更新建议.

优点 & 缺点

优点

  • 自动提取已完成轨道中的知识
  • 更新知识库中的新模式和错误解决方案
  • 基于轨道执行数据提出工作流程改进建议
  • 历史见解优化 futrue 轨道计划

缺点

  • 可能需要对提取出的模式和错误进行手动复查
  • 仅限于分析已完成轨道的数据
  • 有效性取决于轨道执行数据的质量

评测

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问答

Can I use this alongside other Claude Code plugins?

Yes. SupaConductor uses the /orchestrator-supaconductor: namespace and doesn't conflict with any other plugins, built‑in commands, or MCP servers.

Asked by Jamal Carter · Apr 9, 2026

Is this overkill for small tasks?

For a quick one‑file fix — yes, just use Claude Code directly. Use SupaConductor when the work touches three or more files, you’d normally plan before coding, you want automated quality checks, or you want the work done right the first time. You can also use individual commands without the full loop.

Asked by Bilal Choudhury · Mar 22, 2026

Does this work with Cursor, Windsurf, or other AI tools?

No — SupaConductor is a Claude Code plugin that requires Claude Code's plugin system (agents, skills, slash commands, hooks). However, the conductor/ directory it creates is just Markdown files. Any AI tool can read them, so you can switch tools later and keep your specs, plans, and documentation.

Asked by Quyen Tran · Mar 8, 2026

How much of my context window does this use?

Skills use progressive disclosure — only ~100 tokens each for metadata. Full instructions load only when activated (typically under 5,000 tokens each). The 39 skills are not loaded all at once. Agents run as separate conversations with their own context windows, so they don't fill up your main conversation. Approximate usage: Orchestrator ~4,000 tokens (active during /go); Planner ~3,000 tokens (during planning); Evaluator ~2,500 tokens each (only when active); Board meeting ~5,000 tokens (on‑demand); Idle ~500 tokens (between steps).

Asked by Renata Silva · Feb 28, 2026

How much does this cost in API credits?

SupaConductor uses the same Claude API as normal Claude Code — it just structures the work more carefully. Because it runs multiple agents (planning, execution, evaluation), it uses roughly 3‑5× the API calls compared to doing everything manually in one conversation. SupaConductor optimizes costs automatically: it uses Opus (the most capable model) for planning and evaluation, and Sonnet (faster, cheaper) for execution tasks. Ways to reduce cost: use /orchestrator-supaconductor:implement if you write specs yourself, skip board meetings for small features (they're opt‑in), or use human‑in‑the‑loop mode to stay in control of scope.

Asked by Diego Fernández · Feb 24, 2026

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