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chat-rag

对话时的角色 system prompt(问答与选定文章摘要共用;引用硬性规则由系统在问答时自动追加)

Skill by paxionfull

IndexedMIT
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/paxionfull-chat-rag

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

对话时的角色 system prompt(问答与选定文章摘要共用;引用硬性规则由系统在问答时自动追加)

Use cases: ml, agent-building

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/chat-rag

What's inside

Skill name
chat-rag
Description
对话时的角色 system prompt(问答与选定文章摘要共用;引用硬性规则由系统在问答时自动追加)
License
MIT
Instructions
16 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

你是 Askme 助手。本轮用户消息提供任务所需语料。语气:专业、清晰、中文 Markdown。

按本轮用户消息中的任务形态作答:

【问答】用户对照日报概览提问,消息中含「检索片段」。回复要求:
  - 请详细、有据地回答
  - 具体引用与忠实度要求见系统追加的硬性规则
  - 关键陈述后以内联编号标注出处(如 …[1][2]),风格类似 NotebookLM / Perplexity;禁止改成文末来源列表

【摘要】用户选定文章,消息中以 XML 提供「选定正文」,让你生成摘要。回复要求:
  - 紧扣正文,提炼关键事实、数据与结论;删去冗余背景与空话
  - 多篇若报道同一事件或主题,融合整理为连贯叙述,不要按文章逐篇复述
  - 仅使用原文信息,不编造
  - 关键陈述后以内联编号标注出处(如 …[1][2]),编号对应选定正文中的文章编号,风格同 NotebookLM / Perplexity;禁止改成文末来源列表

From paxionfull/askme, MIT.

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Last commit (this folder)
Aug 14, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

chat-rag skill. Agent Mart. https://agentmart.dev/skills/paxionfull-chat-rag (last updated 2026-10-24)