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reflect

Capture and classify conversation patterns into structured learnings for future sessions.

1|Updated Apr 18, 2026
Search Tags:#decisions#learning#patterns#history#confidence#conversations#reflect
One-click install
npx skills add https://github.com/DeDuva/squad --skill reflect-deduva
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: reflect
Source: https://github.com/DeDuva/squad/tree/main/packages/squad-cli/templates/skills/reflect
Command: npx skills add https://github.com/DeDuva/squad --skill reflect-deduva

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Reflect captures high/medium/low confidence patterns from conversations to prevent repeating mistakes and preserve successful learnings across sessions.

Core Features & Use Cases

  • Integrates with .squad/agents/{agent}/history.md and .squad/decisions.md to store learnings.
  • Automatically classifies corrections, praise, and edge cases into actionable learnings.
  • Supports session-driven reflection and post-session consolidation to improve decision making.

Quick Start

Analyze the latest user-agent interaction and extract HIGH/MEDIUM/LOW confidence patterns for future reference.

Frequently Asked Questions about reflect

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I capture conversation learnings to prevent repeating mistakes across sessions?▼

Capture conversation learnings by applying multi-phase flow to identify, analyze, and persist corrections, praise, and edge cases into agent histories and team decisions to prevent repeating mistakes.

What is the best way to log corrections and praise during active agent sessions?▼

Log corrections and praise during active sessions by identifying high, medium, and low confidence patterns, then proposing and persisting them to agent histories and team decisions.

How does conversation reflection classify learning patterns for future reference?▼

Conversation reflection classifies learning patterns by analyzing user-agent interactions and assigning high, medium, or low confidence levels to extract actionable learnings for future reference.

Do I need structured frontmatter metadata to integrate conversation learnings with agent histories?▼

Yes, structured frontmatter metadata in SKILL.md is required to integrate captured conversation learnings with .squad/agents/{agent}/history.md and .squad/decisions.md files.

Can I consolidate post-session learnings to improve team decision making?▼

Yes, session-driven reflection supports post-session consolidation by promoting extracted learnings to team decisions, agent histories, or skill notes to improve decision making.

What are the limitations of relying on confidence patterns for conversation history?▼

Relying on confidence patterns requires a multi-phase flow for identification, analysis, proposal, and persistence, meaning learnings are not automatically applied without this structured workflow.

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