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tianyidatascience

humanize

作者 Tianyi · GitHub ↗ · v0.1.6 · MIT-0
cross-platform ✓ 安全检测通过
160
总下载
0
收藏
0
当前安装
7
版本数
在 OpenClaw 中安装
/install self-evolving-humanize-zh
功能描述
Use this skill when the user wants to generate or optimize Chinese communication copy so it sounds more human, more natural, less templated, and less like po...
安全使用建议
This skill appears to do what it claims: it bootstraps a local Python venv, downloads a Hugging Face reranker, invokes a local or host LLM (CoPaw bridge or a local HTTP endpoint), and iteratively optimizes Chinese copy. Before installing or running: - If you care about privacy, avoid passing secrets or sensitive data in the user prompt—the skill's preservation rule explicitly forwards the entire user request verbatim to the local generation/scoring pipeline (and to any configured HTTP endpoint). If you set HUMANIZE_LLM_BASE_URL to a remote service, your input will be sent there. - The bootstrap step downloads models and installs Python packages into a dedicated venv under your CoPaw working dir; ensure you have disk space and trust the source. The repository's default model is from Hugging Face (BAAI/bge-reranker-v2-m3). - The install_to_copaw.py script copies files into ~/.copaw skill_pool and workspace skills and can enable the skill in the workspace manifest—only run that if you want the skill persistently installed in CoPaw. - The skill reads local CoPaw logs to autodetect endpoints and will attempt to call your host active model; this is normal for local integration but means it reads files under your CoPaw working dir. If you want minimal exposure, run the CLI locally in an isolated environment (skip running install_to_copaw.py) and avoid configuring a remote HUMANIZE_LLM_BASE_URL. Review the repository (especially scripts/bootstrap_runtime.py, scripts/install_to_copaw.py, and scripts/local_generation.py) before running to verify it matches your security expectations.
功能分析
Type: OpenClaw Skill Name: self-evolving-humanize-zh Version: 0.1.6 The skill is a sophisticated Chinese text optimization tool that uses a local scoring model (BGE Reranker) and an iterative refinement loop. It includes automated environment setup (venv creation) and model downloading from Hugging Face (BAAI/bge-reranker-v2-m3), which are standard for local AI tasks. The code logic in scripts like `run_from_brief.py` and `scoring_core.py` is consistent with the stated purpose of 'humanizing' AI-generated text, and no evidence of malicious behavior, data theft, or unauthorized remote access was found.
能力标签
crypto
能力评估
Purpose & Capability
The skill is a local CLI-driven copy-optimization tool that bootstraps a Python runtime, downloads a local reranker model, calls a host LLM (via CoPaw bridge or a local HTTP endpoint), generates candidates, and scores them. The files, scripts, and optional environment variables align with that purpose. There are no unrelated credentials or surprising external services required by default.
Instruction Scope
The runtime instructions require agents to invoke the CLI with the user's full request verbatim and to relay any final-marked output exactly. The code also attempts to autodiscover a local model endpoint (parsing a local copaw.log) and will read/write run folders under the CoPaw working dir. These behaviors are coherent for an offline/local optimization tool but do mean the skill will carry and expose the raw user input to the local model pipeline and will read local CoPaw logs to discover endpoints.
Install Mechanism
No remote binary install spec in the skill manifest; bootstrapping creates a dedicated venv and downloads the specified Hugging Face scoring model (BAAI/bge-reranker-v2-m3). The model source (Hugging Face) and typical Python dependencies are explicit in requirements.lock. No obscure download URLs or URL shorteners are used in the code shown.
Credentials
The skill declares no required environment credentials. It reads optional environment variables (HUMANIZE_GENERATION_BACKEND, HUMANIZE_LLM_BASE_URL, HUMANIZE_LLM_MODEL, COPAW_WORKING_DIR, etc.) to select generation backends; these are reasonable for choosing a local model endpoint. There are no requests for unrelated cloud secrets. Note: if you point HUMANIZE_LLM_BASE_URL at a remote HTTP endpoint, user input will be sent to that endpoint.
Persistence & Privilege
always:false and the skill does not demand elevated platform privileges. The optional installer script (scripts/install_to_copaw.py) will copy the repo into ~/.copaw skill_pool and workspace skills and will modify the workspace skill manifest to mark the skill (optionally) enabled. That is expected for an installer but does write to the host agent's workspace configuration, so run that step only if you trust the skill and want it installed into your CoPaw workspace.
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 self-evolving-humanize-zh
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /self-evolving-humanize-zh 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
v0.1.6
Fix generic service/support reply routing so refund and after-sales rewrite cases use short communication candidates before longform copy heuristics, preserving the service issue and avoiding baseline fallback.
v0.1.5
Default max_rounds is now 3, add --max-rounds/HUMANIZE_MAX_ROUNDS docs, continue retryable repairs within the round budget, and improve common customer-service template cleanup.
v0.1.4
Strengthen final process relay so agents return the full visible optimization report instead of summarizing.
v0.1.3
Improve GitHub README quick start and keep Hub package docs in sync.
v0.1.2
Improve Chinese search metadata while keeping the CoPaw install name as humanize.
v0.1.1
Fix display name so CoPaw installs the skill as humanize; document stable ClawHub and GitHub tag import URLs.
v0.1.0
Initial release: AutoResearch-style Chinese copy humanization skill with visible scoring process.
元数据
Slug self-evolving-humanize-zh
版本 0.1.6
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 7
常见问题

humanize 是什么?

Use this skill when the user wants to generate or optimize Chinese communication copy so it sounds more human, more natural, less templated, and less like po... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 160 次。

如何安装 humanize?

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

humanize 是免费的吗?

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

humanize 支持哪些平台?

humanize 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 humanize?

由 Tianyi(@tianyidatascience)开发并维护,当前版本 v0.1.6。

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