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clarkchenkai

Memory Taxonomist

作者 Cubic AI · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install memory-taxonomist-clarkchenkai
功能描述
Memory Taxonomist — Structured Memory Skill for Turning Raw Notes into Stable Knowledge. Use it when the user needs a disciplined protocol and fixed output c...
使用说明 (SKILL.md)

Memory Taxonomist — Structured Memory Skill for Turning Raw Notes into Stable Knowledge

Use this skill when the task matches the protocol below.

Activation Triggers

  • new notes or transcripts that mix multiple information types
  • agent memory design or memory cleanup work
  • meeting outputs that contain decisions, preferences, and open questions together
  • requests to store user context safely for future retrieval
  • cases where retrieval quality matters more than storage volume

Core Protocol

Step 1: Break input into atomic claims

Do not classify a whole paragraph as one memory object when it contains multiple types.

Step 2: Classify each unit

Sort it into fact, preference, procedure, unresolved question, or exception.

Step 3: Separate durable from provisional

Do not let recent mention automatically become durable truth.

Step 4: Flag conflicts and edge cases

Identify contradictions, overrides, and one-off exceptions before writing memory.

Step 5: Recommend the right storage action

Store, update, deprecate, or hold for clarification based on memory type and certainty.

Output Contract

Always end with this six-part structure:

## Facts
[...]

## Preferences
[...]

## Procedures
[...]

## Unresolved Questions
[...]

## Exceptions
[...]

## Recommended Storage Action
[...]

Response Style

  • Prefer clean classification over verbose summary.
  • Treat unresolved questions as first-class memory objects.
  • Do not convert preferences into universal rules.
  • Call out exceptions instead of hiding them in procedures or facts.

Boundaries

  • It does not store everything by default; some information should remain ephemeral.
  • It does not confuse recency with importance.
  • It does not turn uncertain statements into durable facts without evidence.
安全使用建议
This skill appears coherent and low-risk: it only contains instructions for classifying notes and requires no installs or secrets. Before installing, confirm your agent's memory storage backend and access controls (where the skill's recommended storage actions will be applied) are trustworthy, since the skill's output is intended to be written into your agent's memory system. Also be aware implicit invocation is allowed, so the agent may use this skill automatically when it detects matching triggers.
功能分析
Type: OpenClaw Skill Name: memory-taxonomist-clarkchenkai Version: 1.0.0 The skill bundle is a purely instructional framework designed to help an AI agent categorize and structure raw notes into a specific taxonomy (facts, preferences, procedures, etc.). It contains no executable code, no network access requests, and no instructions that attempt to exfiltrate data or bypass security boundaries. All files, including SKILL.md and the configuration in agents/openai.yaml, are strictly aligned with the stated purpose of information organization and memory management.
能力评估
Purpose & Capability
Name, description, and included reference docs all describe the same task (breaking notes into facts, preferences, procedures, unresolved questions, and exceptions). There are no extra binaries, env vars, or unrelated requirements.
Instruction Scope
SKILL.md instructs only how to parse and classify input and how to format output; it does not ask the agent to read unrelated files, access credentials, or send data to external endpoints.
Install Mechanism
No install spec and no code files beyond documentation means nothing is written to disk or fetched at install time.
Credentials
No environment variables, credentials, or config paths are requested; required privileges are proportional to the stated purpose.
Persistence & Privilege
always:false (good). agents/openai.yaml sets allow_implicit_invocation: true, which means the agent may call this skill automatically when triggers match; this is normal for skills but you should be aware the agent could invoke it without an explicit user command when relevant.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install memory-taxonomist-clarkchenkai
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /memory-taxonomist-clarkchenkai 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of the Memory Taxonomist skill. - Provides a structured protocol for turning raw notes into stable, classified knowledge. - Breaks down input into atomic claims, classifies each as fact, preference, procedure, unresolved question, or exception. - Emphasizes careful separation of durable and provisional information, flagging conflicts and exceptions. - Outputs results in a fixed six-part markdown structure for clear, consistent memory storage and retrieval. - Designed for disciplined knowledge management when retrieval quality is prioritized over storage volume.
元数据
Slug memory-taxonomist-clarkchenkai
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Memory Taxonomist 是什么?

Memory Taxonomist — Structured Memory Skill for Turning Raw Notes into Stable Knowledge. Use it when the user needs a disciplined protocol and fixed output c... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 81 次。

如何安装 Memory Taxonomist?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install memory-taxonomist-clarkchenkai」即可一键安装,无需额外配置。

Memory Taxonomist 是免费的吗?

是的,Memory Taxonomist 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Memory Taxonomist 支持哪些平台?

Memory Taxonomist 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Memory Taxonomist?

由 Cubic AI(@clarkchenkai)开发并维护,当前版本 v1.0.0。

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