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独立思考五部曲

v5.0.0

独立思考五部曲。触发场景:**架构讨论、排错、复盘、决策、不确定知识点**。日常闲聊、确认、打招呼、简单问答 → 直接回答,不查向量、不 thinking、不走五步曲。与沟通五部曲并行通用。

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for markma84/independent-thinking-5steps.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "独立思考五部曲" (markma84/independent-thinking-5steps) from ClawHub.
Skill page: https://clawhub.ai/markma84/independent-thinking-5steps
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Canonical install target

openclaw skills install markma84/independent-thinking-5steps

ClawHub CLI

Package manager switcher

npx clawhub@latest install independent-thinking-5steps
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Purpose & Capability
The skill is an instruction-only 'independent thinking' workflow, which is reasonable as prose. However, it mandates calling a local script at a hardcoded absolute path (/Users/markma01/.openclaw/workspace/scripts/query_vector.py) and to use ChromaDB, yet the skill declares no required binaries, environment variables, or config paths. Requiring a specific local script and DB without declaring them is disproportionate and inconsistent with the stated metadata.
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Instruction Scope
SKILL.md explicitly forces the agent to run a local Python script at a absolute user-specific path and forbids alternate invocation patterns. It also demands 'permanently disable system Memory Search' and 'only use the exclusive backend vector system' and requires writing 'look' outputs back into a wiki. These instructions reach into local filesystem, agent runtime behavior, and platform features without providing configuration, fallback, or justification, giving the skill broad operational influence beyond a simple decision workflow.
Install Mechanism
No install spec or code files are present (instruction-only), so nothing is written to disk by the skill itself. This lowers installation risk, but the runtime instructions still expect a local script and a ChromaDB backend that are not supplied.
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Credentials
The skill asks (in practice) for access to a local script and a vector DB and asks to disable a system feature, but declares no required env vars, credentials, or config paths. That mismatch is disproportionate: the skill's operation depends on resources and potential privileges (local filesystem execution and wiki persistence) that are not declared or explained.
Persistence & Privilege
The skill does not set always:true and does not request persistent installation. However, it instructs the agent to '永久禁用系统自带 Memory Search' (permanently disable system Memory Search) and to persist outputs into a wiki for future use. Asking the agent to alter platform behavior and to write persistent knowledge is a non-trivial privilege implication even without always:true; verify what agent/platform-level actions are actually possible before trusting this instruction.
What to consider before installing
This skill is an instruction-only workflow that mandates running a local Python script at /Users/markma01/.openclaw/workspace/scripts/query_vector.py, using ChromaDB, disabling the system Memory Search, and writing results into a wiki — yet it declares no files, env vars, or config paths. Before installing or enabling it: (1) confirm you have the referenced query_vector.py and ChromaDB configured, or update the skill to point to your environment; (2) do not permit it to change platform-level features (like disabling Memory Search) unless you control and understand the platform; (3) verify where the wiki writes go and what permissions are required; (4) prefer running this in a sandboxed agent instance while testing; (5) if you cannot map the hardcoded path to your environment, treat the skill as incompatible or request the author to parameterize paths and explain required credentials.

Like a lobster shell, security has layers — review code before you run it.

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58downloads
0stars
1versions
Updated 1w ago
v5.0.0
MIT-0

独立思考五部曲

底层核心准则 · 与沟通五部曲同级并行 自验驱动的深度决策方法论

核心定位

自验 = 用自己过去的总和(向量+wiki)替代当下他人在场

独立思考五部曲是沟通五部曲的"镜像"——结构相同,验证介质不同:

  • 沟通五部曲 → 他验(对方实时反馈)
  • 独立思考五部曲 → 自验(向量+wiki 历史知识库)

五步法结构(听→想→说→做→看)

1. 听:直觉接收

接收问题/刺激,让直觉碎片在模糊空间自由碰撞,等待模式自然浮现。

2. 想:向量溯源 + wiki扩展

开口/动手前,先向量检索历史经验和踩坑教训,再 wiki 扩展连接到已有知识网络,形成全局独立判断。

向量调用规范(强制):

# 唯一正确格式
python3 /Users/markma01/.openclaw/workspace/scripts/query_vector.py "<检索词>"

# 禁止以下所有格式
cd /path && python3 script.py
echo "query" | python3 script.py

3. 说:有据表达 + wiki校验

将思考结论结构化输出,同步 wiki 校验论点是否与已有知识对齐,逻辑连贯、不主观臆断。

注意:独立思考的"说"不是汇报(无实时对方),而是将脑内推理外化为可供后续追溯的书面结论。

4. 做:向量校验

执行前用向量核对步骤、风险与适配方案,完成自检后再动手。

5. 看:wiki 知识关联

复盘时检索 wiki 连接已有经验,把新经验织入知识网络,防止重复踩坑。


检查点矩阵

阶段检查点他验/自验
直觉接收,等待模式浮现自验
向量溯源 + wiki扩展自验
wiki连接已有论点自验
向量核对步骤自验
wiki连接已有经验自验

强制执行规则

  1. 仅在触发场景下执行(架构讨论、排错、复盘、决策、不确定知识点)
  2. 日常闲聊、确认、打招呼、简单问答 → 直接回答,不查向量、不 thinking、不走五步曲
  3. 永久禁用系统自带 Memory Search,仅使用专属后台向量系统(query_vector.py / ChromaDB)
  4. 「看」的输出必须闭环存入 wiki,为下次「想」提供素材
  5. 适时触发:复杂任务全程检查点,简单任务降低检查点密度

与沟通五部曲的关系

维度沟通五部曲独立思考五部曲
核心他验自验
验证介质对方实时反馈向量 + wiki 历史知识库
侧重互动、汇报、方案讨论思考、决策、复盘
并行对外沟通用对内思考用

两者合并,才是完整的「想清楚 → 说出来 → 做到位 → 固下来」闭环。


快速触发检查清单

每次开口/动手前自检:

  • 已调用 query_vector.py 检索相关历史经验
  • 「想」的结论有向量事实支撑 + wiki 扩展
  • 「说」的论点已 wiki 校验
  • 「做」的方案经向量校验无已知风险
  • 「看」的结果已连接 wiki 并计划存入

本 skill 为小蜂独立思考核心准则,与「沟通五部曲」同级并行。 v5.0(2026-04-17):升级为五部曲,融入 wiki 检查点,厘清他验/自验定位

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