Retrospective Agent (Grade A) logo

Retrospective Agent (Grade A)Security-tested data-ai skill for Claude AI. Grade A. Runs after every track completion to extract learnings. Analyzes what worked, what failed, and what patterns emerged. Updates conductor/knowledge/

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Daniel NikulshynReviewed by Daniel Nikulshyn·Updated July 2026

Overview

The Retrospective Agent is a data-ai skill designed for Claude AI. It runs after every track completion to extract learnings, analyzing what worked, what failed, and what patterns emerged. The skill updates the conductor/knowledge/patterns.md file with new solutions and the errors.json file with new error patterns. It also proposes skill updates if workflow improvements are identified. The Retrospective Agent automatically triggers after a track reaches COMPLETE status. The tool's workflow involves analyzing track execution data, extracting patterns from completed work, detecting error patterns, identifying skill improvements, and updating the knowledge base. It reviews the track's plan, execution summary, tasks, commits, spec, and metadata. The Retrospective Agent updates the knowledge base by adding new patterns to the patterns.md file and new error patterns to the errors.json file. The skill is triggered automatically by the orchestrator after every track completion, providing a continuous learning experience for future tracks. The Retrospective Agent helps to refine the skill by extracting reusable solutions, error patterns, and skill improvements, which can be used to make future tracks smarter.

Key features

  • Track execution analysis
  • Pattern extraction and documentation
  • Error pattern identification and solutioning
  • Skill improvement proposals
  • Knowledge base updates

Pricing

Model
Free
Category
Skills
Rating
No reviews yet

Use cases

Post-Track Review

Run the Retrospective Agent after completing a track to extract learnings and update the knowledge base.

Workflow Optimization

Use the Retrospective Agent to identify areas for workflow improvement and propose skill updates.

Pros & Cons

Pros

  • Automatically extracts learnings from completed tracks
  • Updates knowledge base with new patterns and error solutions
  • Proposes workflow improvements based on track execution data
  • Enhances future track planning with historical insights

Cons

  • May require manual review of extracted patterns and errors
  • Limited to analyzing data from completed tracks
  • Effectiveness depends on quality of track execution data

Reviews

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Q&A

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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