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🤖🤝🧠 better collab with your agent
作者
Sebastian Otálora
· GitHub ↗
· v1.0.0
1765
总下载
3
收藏
2
当前安装
1
版本数
在 OpenClaw 中安装
/install user-cognitive-profiles
功能描述
Analyze ChatGPT conversation exports to discover cognitive archetypes and optimize AI-human communication patterns. Enables personalized agent interactions based on detected user profiles.
安全使用建议
This package mostly does what it says — it analyzes your ChatGPT export locally and produces a profile — but there are a few things to check before running: 1) Review requirements.txt vs SKILL.md: decide whether you want to install scikit-learn/numpy/PyYAML (they are listed as core deps in requirements.txt but described as optional/recommended in the docs). 2) Be cautious with test_wildchat.py — it loads a large external dataset (allenai/WildChat-1M) via the datasets library and will perform network I/O; don't run it if you want strictly local processing. 3) The tool writes output and may create ~/.openclaw/* files; inspect those paths or change them to a location you control. 4) Inspect the scripts if you have sensitive data: the analyzer code appears local (no hidden remote endpoints), but always examine third-party dependencies you install. Recommended: run the analyzer in an isolated virtualenv (or container), review scripts/analyze_profile.py and test_wildchat.py yourself, and avoid running test scripts that pull external datasets unless you intend to.
功能分析
Type: OpenClaw Skill
Name: user-cognitive-profiles
Version: 1.0.0
The skill `user-cognitive-profiles` is designed for local analysis of ChatGPT conversation exports to identify user cognitive archetypes. The `SKILL.md` and `README.md` provide clear, benign instructions for the user and do not contain any prompt injection attempts against the OpenClaw agent. The core scripts (`analyze_profile.py`, `compare_profiles.py`) perform local file I/O for input/output (e.g., `conversations.json`, `profile.json`) and do not exhibit any network communication, arbitrary shell execution, or access to sensitive system files. The `test_wildchat.py` script legitimately accesses the public 'allenai/WildChat-1M' dataset for testing purposes, which is not a security concern. All processing is local, aligning with the privacy claims in the documentation.
能力评估
Purpose & Capability
The name/description match the code: scripts analyze ChatGPT conversation exports and produce a profile to tune agents. Requesting python3 is appropriate. Minor inconsistency: SKILL.md/README state that only the standard library is required (scikit-learn/numpy are listed as recommended), but requirements.txt lists scikit-learn, numpy, and PyYAML as core dependencies — unclear which packages are actually required for normal runs.
Instruction Scope
Primary runtime instructions (export ChatGPT data, run scripts/analyze_profile.py) are coherent and limited to local processing of conversations.json. However: (1) the package includes test_wildchat.py which instructs downloading/streaming the external 'allenai/WildChat-1M' dataset (network activity and third‑party data access) but SKILL.md doesn't mention this test script; (2) the scripts write output to a home config path (~/.openclaw/...), which the metadata did not declare as a required config path. These are scope surprises rather than obvious malicious behavior.
Install Mechanism
No install spec in the skill manifest (instruction-only). There is a requirements.txt and README instructs 'pip3 install -r requirements.txt' — that will install scikit-learn/numpy/PyYAML per the file. This is a normal Python dependency install, but the manifest's claim that only the standard library is required contradicts requirements.txt. No remote or obfuscated installers were found; the package appears to rely on standard PyPI packages.
Credentials
The skill does not request environment variables or credentials. It processes local ChatGPT exports and generates a JSON profile. One proportionality note: scripts and SKILL.md write output to ~/.openclaw/my-cognitive-profile.json and allow creating ~/.openclaw/my-archetypes.yaml — the manifest did not list required config paths, so users should be aware the tool will create/read files in the user's home directory.
Persistence & Privilege
The skill does not request always:true, elevated privileges, or modify other skills. It is user-invocable and can be run locally. Autonomous invocation is allowed by default for skills on the platform, but nothing in the package indicates forced or hidden persistence.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install user-cognitive-profiles - 安装完成后，直接呼叫该 Skill 的名称或使用
/user-cognitive-profiles触发 - 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 – analyze ChatGPT conversations to identify cognitive archetypes and optimize AI-human communication.
- Processes exported ChatGPT conversation history to detect user communication patterns.
- Generates a cognitive profile output (JSON) with archetype breakdowns, communication metrics, and actionable insights.
- Supports configuration of custom archetypes and adjustable analysis granularity.
- Enables integration with OpenClaw agent profiles for personalized AI interactions.
- All analysis runs locally; no data is uploaded or shared automatically.
元数据
常见问题
🤖🤝🧠 better collab with your agent 是什么？
Analyze ChatGPT conversation exports to discover cognitive archetypes and optimize AI-human communication patterns. Enables personalized agent interactions based on detected user profiles. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 1765 次。
如何安装 🤖🤝🧠 better collab with your agent？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install user-cognitive-profiles」即可一键安装，无需额外配置。
🤖🤝🧠 better collab with your agent 是免费的吗？
是的，🤖🤝🧠 better collab with your agent 完全免费（开源免费），可自由下载、安装和使用。
🤖🤝🧠 better collab with your agent 支持哪些平台？
🤖🤝🧠 better collab with your agent 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 🤖🤝🧠 better collab with your agent？
由 Sebastian Otálora（@sebastianffx）开发并维护，当前版本 v1.0.0。
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