reflect

Convert session corrections and factual errors into guardrail SKILL.md entries.

Updated Mar 1, 2026
One-click install
npx skills add https://github.com/hve4638/hve-cc-marketplace --skill reflect-hve4638
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: reflect
Source: https://github.com/hve4638/hve-cc-marketplace/tree/main/common/skills/reflect
Command: npx skills add https://github.com/hve4638/hve-cc-marketplace --skill reflect-hve4638

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Extract user corrections and factual errors from the session, and turn each item into a child guardrail skill (reflect-<slug>/SKILL.md). In future sessions the children auto-trigger via description matching and prevent the same mistake.

Core Features & Use Cases

  • Reflect vs children: reflect performs retrospective thinking; children are auto-trigger candidates that carry only future-facing instructions.
  • The four retrospection slots are internal thinking aids and must not appear in child output.
  • Storage spec: path, child prefix, language requirements, and slug constraints.
  • Self-exploration principle: retrospective extraction relies only on session context; external lookups are avoided.
  • Retrospection categories: Points corrected; misknown or outdated facts.

Quick Start

Run reflect after a session to generate child reflect-<slug>/SKILL.md entries from user corrections and factual errors.

Frequently Asked Questions about reflect

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

FAQPage Schema
How do I turn session corrections into automated guardrails for AI?

The reflect skill identifies user corrections and factual errors from a session and converts each item into a child SKILL.md file with a Rule body and a Not a violation section. These child skills then auto-trigger in future sessions via description matching to prevent the same mistakes.

What is retrospection in AI safety and how does session correction work?

Retrospection in AI safety is the process of extracting points corrected and misknown or outdated facts from a session's context. The reflect skill uses this retrospective thinking to generate future-facing child skills that automatically prevent repeated errors without relying on external lookups.

How do I generate child skills from a chat session to prevent future mistakes?

Run the reflect skill after a session to generate child reflect-<slug>/SKILL.md entries from user corrections and factual errors. Each entry requires a frontmatter with name and description, enforces kebab-case slugs, and is stored under .claude/skills/reflect-<slug>/SKILL.md.

Does the reflect skill require external lookups to extract session corrections?

No, the reflect skill follows a self-exploration principle where retrospective extraction relies only on session context. External lookups are avoided, ensuring that guardrail rules are generated strictly from the interactions within the current session.

What are the limitations of using auto-triggering child skills for AI safety guardrails?

A limitation is that child skills only carry future-facing instructions and must not include the four internal retrospection slots. Additionally, the generated catalog acts as the single source of truth, requiring proper kebab-case slug formatting and frontmatter to function correctly.