conversation_to_prompt

Convert task conversations into reusable system prompt drafts with structured quality checks.

772|135|Updated Jan 10, 2026
One-click install
npx skills add https://github.com/wecode-ai/Wegent --skill conversation-to-prompt
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: conversation_to_prompt
Source: https://github.com/wecode-ai/Wegent/tree/main/backend/init_data/skills/conversation_to_prompt
Command: npx skills add https://github.com/wecode-ai/Wegent --skill conversation-to-prompt

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

After a productive AI collaboration session, the useful working preferences and task methods discovered during the conversation are lost. This Skill distills a full task conversation into a reusable system prompt draft so future sessions start with the same effective instructions.

Core Features & Use Cases

  • Conversation Analysis: Extracts stable collaboration preferences and reusable task methods while filtering out one-off project details.
  • Structured Prompt Generation: Produces a prompt following a fixed structure covering assistant identity, working style, task principles, and output requirements.
  • Multi-Stage Quality Control: Drafts, evaluates, and rewrites the prompt against explicit rejection rules to avoid summary-style or vague outputs.
  • Use Case: After a long debugging session where the AI learned your preferred code review style and testing workflow, convert that conversation into a system prompt you can reuse for future coding tasks.

Quick Start

Convert this conversation into a reusable system prompt that captures my collaboration preferences and task methods.

Frequently Asked Questions about conversation_to_prompt

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

FAQPage Schema
How do I turn a chat conversation into a reusable system prompt?▼

Provide the normalized conversation messages and let the skill analyze them for stable collaboration preferences and reusable task methods. It generates a structured prompt draft, evaluates it against quality rules, and rewrites it until it passes.

What structure does the generated system prompt follow?▼

The prompt starts with the assistant identity and core responsibility, followed by working style preferences, task-handling principles, and output requirements. This fixed structure is mandatory and drafts that deviate from it are rejected and rewritten.

Does the output include markdown or JSON formatting?▼

No. The output protocol strictly forbids markdown code fences, JSON objects, and any explanatory text before or after the prompt. The result is a plain text prompt body that can be used directly as a system prompt.

How does the skill avoid leaking one-off project details into the prompt?▼

During the analysis stage, the skill explicitly identifies one-off context and temporary decisions for removal. Drafts containing project-specific details are rejected under the evaluation rules and rewritten to keep only reusable instructions.

What are the limitations of conversation-to-prompt generation?▼

The skill is prompt-only orchestration with no external tools, so quality depends on the conversation containing clear, stable preferences. Short or highly task-specific conversations may yield generic prompts with limited reusable content.