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rag-skill
by
xiaochengzhen
· GitHub ↗
· v1.0.4
· MIT-0
104
Downloads
0
Stars
2
Active Installs
5
Versions
Install in OpenClaw
/install rag-skill
Description
当用户需要从知识库获取 RAG 相关内容时使用,知识库中汇聚了20位艺术家深度档案，科技与艺术的交汇，大致包括1、塞德里克·索恩 (Cedric Thorne) ------ 磁场雕塑与"无形张力"2. 月见里 薰 (Kaoru Tsukimisato) ------ 纳米绘画与"微观宇宙"3. 奥利维亚·斯特林...
Usage Guidance
This skill contacts a remote Prana service (https://claw-uat.ebonex.io) and requires you to provide an API key via the PRANA_SKILL_API_FLAG environment variable. The bundled scripts will not fetch keys for you — SKILL.md requires you to explicitly confirm before obtaining a key and to choose whether the key is set temporarily (session) or persisted globally. Before installing/using: 1) verify you trust the endpoint (note it is a 'uat' host), 2) prefer temporary/session env vars if you do not want a persistent credential stored globally, and 3) follow the SKILL.md confirmation steps exactly (it forbids re-fetching or overwriting PRANA_SKILL_API_FLAG if already present). If you are unsure about persisting the key, decline global storage and use the temporary-session option.
Capability Tags
Capability Assessment
Purpose & Capability
Name/description (RAG knowledge retrieval) align with included client scripts and declared network endpoints (agent-run, agent-result). Requiring a single PRANA_SKILL_API_FLAG x-api-key is proportional to the described remote-agent workflow.
Instruction Scope
SKILL.md contains a strict, stepwise process (check env var → possibly GET api_key → set PRANA_SKILL_API_FLAG → run client). The instructions stay within the stated purpose, but they impose explicit user-confirmation and environment-writing rules; they do not ask the agent to read arbitrary files or other credentials.
Install Mechanism
No install spec (instruction-only). Two thin client scripts are bundled (JS and Python) that make HTTP calls to the service. No downloads from external/untrusted URLs or installers are present.
Credentials
Only PRANA_SKILL_API_FLAG is required, which is appropriate for an x-api-key header. However the skill explicitly supports persisting the key as a global environment/config entry — this is sensitive and should be chosen consciously by the user.
Persistence & Privilege
always:false and normal agent invocation. The skill encourages writing a global env/config value (openclaw config set ...) which grants persistent credential presence; this is not required but offered as a convenience and should be consented to by the user.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install rag-skill - After installation, invoke the skill by name or use
/rag-skill - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.4
No file/content changes detected in this version.
- No updates or modifications; this release maintains previous functionality and documentation.
- Version number incremented for administrative purposes only.
v1.0.3
**Changelog for rag-skill v1.0.3**
- Expanded the skill's description to include a summary of the 20 featured artists and their cross-disciplinary technological-artistic themes in the knowledge base.
- No file or network logic changes; only the skill description was updated to provide more specific knowledge context.
- The step-by-step process, environment handling, and API usage remain unchanged.
v1.0.2
- The skill description was greatly simplified, removing detailed knowledge base content and artist examples.
- The skill name in the markdown heading changed from "知识库检索" to "RagFlow知识库检索".
- All file and functional logic remain unchanged; no code changes were detected.
- Documentation and process rules were cleaned up, but critical step-by-step usage flows and access constraints remain the same.
- Overall, this release makes documentation more concise and focused while maintaining essential operational requirements.
v1.0.1
- 技能名称由“RagFlow知识库检索”更改为“知识库检索”。
- description 更新，新增具体20位艺术家的深度档案、艺术与科技交汇内容说明，提升了领域背景介绍。
- 原有功能和使用流程保持一致，主要加强了描述性内容的丰富度和场景化表达。
- 没有检测到任何文件代码更改，仅文档说明更新。
v1.0.0
RagFlow知识库检索 1.0.0
- Initial release of the RagFlow知识库检索 skill for retrieving RAG-related information from a remote knowledge base via the Prana agent platform.
- Implements a strict, multi-step usage process requiring explicit user confirmation to fetch and set the `api_key`, with clear separation of temporary and global environment options.
- Enforces process integrity: prohibits merging or skipping steps, or re-fetching keys if the environment variable is already set.
- Includes clear rules for presenting output and error messages, and restricts history/record queries to explicit user requests only.
- Designed for research and investment scenarios needing rapid RAG knowledge base access.
Metadata
Frequently Asked Questions
What is rag-skill?
当用户需要从知识库获取 RAG 相关内容时使用,知识库中汇聚了20位艺术家深度档案，科技与艺术的交汇，大致包括1、塞德里克·索恩 (Cedric Thorne) ------ 磁场雕塑与"无形张力"2. 月见里 薰 (Kaoru Tsukimisato) ------ 纳米绘画与"微观宇宙"3. 奥利维亚·斯特林... It is an AI Agent Skill for Claude Code / OpenClaw, with 104 downloads so far.
How do I install rag-skill?
Run "/install rag-skill" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is rag-skill free?
Yes, rag-skill is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does rag-skill support?
rag-skill is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created rag-skill?
It is built and maintained by xiaochengzhen (@xiaochengzhen); the current version is v1.0.4.
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