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在 OpenClaw 中安装
/install paper-anonymizer-academic-pdf-redaction
功能描述
Redact text from PDF documents for blind review anonymization
安全使用建议
This is a coherent, instruction-only guide for redacting PDFs locally. Before using it: (1) Test on copies of documents — the verify function and thresholds are inconsistent (80% vs 70%) and the 1000-character check may be inappropriate for short papers. (2) Update pattern handling to use proper regular expressions when needed (PyMuPDF's page.search_for() expects literal text; wildcard patterns like '*@*.edu' won't work as written). (3) Be careful with the 'References' detection heuristic (it can misidentify pages). (4) Install PyMuPDF (fitz) from the official package index if you intend to run the code, and review dependency sources. There are no hidden network calls or credential requests in the instructions, but treat this as guidance (not packaged code) and review any code you run locally.
功能分析
Type: OpenClaw Skill
Name: paper-anonymizer-academic-pdf-redaction
Version: 0.1.0
The skill bundle provides legitimate instructions and Python code for redacting academic papers using the PyMuPDF (fitz) library. The code includes safety checks to prevent over-redaction and verify document integrity, with no evidence of data exfiltration, malicious execution, or prompt injection attacks in SKILL.md.
能力评估
Purpose & Capability
Name/description (redact PDFs for blind review) matches the instructions: they show how to find patterns in PDF text and apply redactions. No unrelated credentials, binaries, or config paths are requested.
Instruction Scope
Instructions remain narrowly scoped to opening, searching, redacting, and verifying PDFs locally. Issues: (1) The top-level rule asks to 'Check that 80%+ of original text remains' but the included verify_redaction() raises only if retention < 70% (inconsistent thresholds). (2) Pattern examples (e.g., '*@*.edu') are presented as wildcard patterns, but the sample PyMuPDF code uses page.search_for(pattern) which matches literal text, not shell-style wildcards—this could cause incorrect behavior if copy/pasted. (3) The heuristic for locating the References page (first page containing 'references') can misidentify sections. These are functional correctness concerns, not scope creep or exfiltration.
Install Mechanism
No install spec and no code files — the skill is instruction-only. It recommends using PyMuPDF but does not attempt to download or execute anything itself, minimizing install risk.
Credentials
The skill requests no environment variables, credentials, or config paths. All operations are local file I/O consistent with its purpose.
Persistence & Privilege
always:false and default invocation settings are used. The skill does not request persistent privileges or modify other skills or system configs.
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 paper-anonymizer-academic-pdf-redaction - 安装完成后，直接呼叫该 Skill 的名称或使用
/paper-anonymizer-academic-pdf-redaction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
v0.1.0
Bulk publish from all-task-skills-dedup
元数据
常见问题
academic-pdf-redaction 是什么？
Redact text from PDF documents for blind review anonymization. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 82 次。
如何安装 academic-pdf-redaction？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install paper-anonymizer-academic-pdf-redaction」即可一键安装，无需额外配置。
academic-pdf-redaction 是免费的吗？
是的，academic-pdf-redaction 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
academic-pdf-redaction 支持哪些平台？
academic-pdf-redaction 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 academic-pdf-redaction？
由 lnj22（@lnj22）开发并维护，当前版本 v0.1.0。
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