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Install in OpenClaw
/install karpathy-query-feedback
Description
Execute Karpathy LLM queries by searching memories via M-Flow, formatting results as wiki entries, and saving them for later compilation.
README (SKILL.md)
Karpathy Query → Wiki 回流 Skill
描述
实现 Karpathy LLM Knowledge Base 的第一阶段：Query → Wiki回流。
当用户发起查询时：
- 使用 M-Flow 搜索相关记忆
- 将结果格式化为 wiki 条目
- 存入 wiki 层供后续 Compile 使用
激活条件
- 用户发起知识查询
- 需要将查询结果回流到 wiki
- session → knowledge pipeline
工作流
用户查询 → M-Flow搜索 → Wiki格式化 → 存入wiki层 → 供Compile使用
Wiki 条目格式
| source | content | tags | timestamp |
|--------|---------|------|-----------|
| session:xxx | 知识内容 | tag1,tag2 | 2026-04-05 |
使用方式
Python API
from karpathy_query_feedback import QueryFeedbackPipeline
pipeline = QueryFeedbackPipeline()
results = await pipeline.query("用户询问的问题")
wiki_entries = pipeline.format_as_wiki(results)
await pipeline.save_to_wiki(wiki_entries)
命令行
python scripts/query_and_save.py "查询内容" --format wiki --output ./wiki/
搜索模式
lexical: BM25 全文搜索（快速、精确）episodic: 向量搜索（语义相似）triplet: 三元组搜索（关系推理）hybrid: 混合搜索（lexical + episodic）
配置
- 使用 M-Flow 作为底层记忆系统
- Wiki 存储路径:
knowledge/wiki/ - 标签体系: 从配置或自动提取
依赖
- m-flow-memory skill (已安装)
- knowledge-distillation skill (用于标签提取)
文件结构
karpathy-query-feedback/
├── SKILL.md
├── scripts/
│ ├── __init__.py
│ ├── pipeline.py # 核心管道
│ ├── formatter.py # Wiki格式化
│ ├── search.py # 搜索封装
│ └── query_and_save.py # CLI入口
└── docs/
└── README.md
Usage Guidance
This skill appears coherent and limited to local memory search and file writes. Before installing: 1) Verify and trust the declared dependency 'm-flow-memory' (the skill dynamically loads and executes that module from disk). 2) Be aware it will create/append files under knowledge/wiki/ in your environment. 3) There are no requested secrets or network calls in the provided code, but if you use this in a shared or production environment, review the m-flow and knowledge-distillation skills for any network or credential usage. If unsure, run it in a sandbox or inspect the m-flow dependency first.
Capability Analysis
Type: OpenClaw Skill
Name: karpathy-query-feedback
Version: 1.0.0
The skill bundle implements a knowledge management pipeline that retrieves information from a memory system (M-Flow) and saves it as formatted Markdown wiki entries. The code in scripts/__init__.py and the various test scripts (test_pipeline.py, debug_search.py) perform standard file I/O and inter-skill communication within the expected OpenClaw environment, with no evidence of data exfiltration, malicious execution, or prompt injection.
Capability Assessment
Purpose & Capability
Name/description (Karpathy Query → Wiki回流) match the implementation: the pipeline searches an M‑Flow memory, converts results to WikiEntry objects, and saves them under knowledge/wiki/. Declared dependency on m-flow-memory is appropriate for this functionality.
Instruction Scope
SKILL.md and scripts consistently instruct the agent to use M‑Flow, format entries as markdown table rows, and save them to a local wiki path. The code only reads/writes files under the skill's repo (knowledge/wiki/) and imports the local m-flow skill; there are no instructions to read unrelated system files, environment variables, or to transmit data to external endpoints.
Install Mechanism
No install spec is provided (instruction/code bundle only). There are no downloads or external installers; code is included in the skill. This is the lowest-risk install pattern for this platform.
Credentials
The skill requires no environment variables, credentials, or special config paths. It does dynamically import the m-flow skill from a relative path (declared as a dependency), which is expected and proportional to its purpose.
Persistence & Privilege
The skill creates and appends markdown files under knowledge/wiki/ (self-persistence of produced wiki content). always:false (not force-installed) and it does not modify other skills' configurations, but it will execute code from the local m-flow dependency at runtime via importlib (this is normal for code dependencies—review that dependency before trusting).
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install karpathy-query-feedback - After installation, invoke the skill by name or use
/karpathy-query-feedback - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: Query to Wiki feedback loop
Metadata
Frequently Asked Questions
What is Karpathy Query Feedback?
Execute Karpathy LLM queries by searching memories via M-Flow, formatting results as wiki entries, and saving them for later compilation. It is an AI Agent Skill for Claude Code / OpenClaw, with 99 downloads so far.
How do I install Karpathy Query Feedback?
Run "/install karpathy-query-feedback" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Karpathy Query Feedback free?
Yes, Karpathy Query Feedback is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Karpathy Query Feedback support?
Karpathy Query Feedback is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Karpathy Query Feedback?
It is built and maintained by sune (@sora-mury); the current version is v1.0.0.
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