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在 OpenClaw 中安装
/install phd-research-companion
功能描述
A complete PhD research lifecycle management system tailored for computer science doctoral students. Supports literature survey (arXiv/DBLP/ACM/IEEE search &...
安全使用建议
Do not run this package on a production or credentialed system yet. Specific concerns:
- The bundle appears incomplete: expected helper files (a 'run' wrapper and create_experiment_design.py) are referenced but not present. Ask the author for the complete package.
- Several Python files contain syntax/formatting problems (malformed BibTeX generation, embedded code blocks inside strings) and brittle constructs (exec'ing partial source in the test suite). These are likely to crash or may execute unexpected local code.
- Background/cron guidance and examples are fine conceptually, but avoid adding cron jobs or running long background processes until the code is fixed and you understand where it writes logs/progress files.
- If you want to try it: do so in a disposable, isolated environment (container or VM) with no sensitive credentials mounted. Inspect and lint the Python files (flake8/pyflakes) and run unit tests in that sandbox. Replace any 'exec(open(...))' usage with safe static checking. Confirm network calls (arXiv/Semantic Scholar/IEEE) are implemented safely and that no hidden endpoints are used before running searches that download PDFs.
- If you cannot get a complete/fixed package from the maintainer, prefer not to install. If you proceed, monitor created files (progress JSON, generated BibTeX/markdown) and avoid running the test suite or install script until you have reviewed and corrected the code.
功能分析
Type: OpenClaw Skill
Name: phd-research-companion
Version: 1.0.2
The PhD Research Companion is a comprehensive research management toolset designed for academic workflows, including literature searching, paper analysis, and LaTeX template generation. While the bundle includes instructions for persistence (cron jobs for daily updates) and broad file system access (searching the workspace for PDFs in scripts/paper_analyzer.py), these actions are consistent with the stated purpose of automating a PhD research environment. The code contains some functional gaps and syntax errors (notably a markdown-in-code artifact in scripts/multi_source_search.py), but there is no evidence of malicious intent, data exfiltration, or unauthorized remote access.
能力评估
Purpose & Capability
The name/description (research lifecycle management) lines up with the shipped scripts (literature search, paper analysis, LaTeX generator, compliance checks, project initializer). However the SKILL.md and scripts reference a 'run' wrapper and other helper scripts (e.g., create_experiment_design.py, a run wrapper) that are not present in the file manifest. Several README/installer/test scripts expect these missing files. This mismatch suggests the bundle is incomplete or packaged incorrectly.
Instruction Scope
Runtime instructions and background docs instruct the agent/user to run long background jobs, cron jobs, and to spawn sub-agents. The scripts write progress files (search-progress-*.json) and other artifacts into project directories and /tmp. There are no requests for external credentials, but the code contains calls to subprocess.Popen (in BACKGROUND-RUN examples) and a test suite that uses exec(open(...).read()...) to run partial file contents — this is brittle and can execute arbitrary local code. Also, multi_source_search.py contains calls to progress_tracker.update without null checks (progress_tracker may be None), and the search module contains TODOs/mock implementations that would need network code to function. Together these point to scope creep and fragile/possibly unsafe runtime behavior if executed as-is.
Install Mechanism
There is no install specification (instruction-only skill). Nothing downloads external code during installation. That reduces supply-chain risk from an install step. However, the package includes Python scripts which will run on demand — the lack of an install step doesn't eliminate runtime risks from the code itself.
Credentials
The skill declares no required environment variables, no credentials, and no config paths. The requested access (filesystem create/read/write within project folders and optional /tmp) is consistent with the described purpose. No secret exfiltration variables are requested.
Persistence & Privilege
always:false and no special platform privileges are requested. The skill describes cron jobs and background runs (user-invoked patterns), which are normal for long-running tasks, but the combination of autonomous background patterns plus the code problems above increases potential impact if misused — though the skill does not request elevated privileges or attempt to modify other skill 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 phd-research-companion - 安装完成后，直接呼叫该 Skill 的名称或使用
/phd-research-companion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
v1.0.2
PhD Research Companion v1.0.2 – Changelog
- Added robust background execution support and monitoring tools (see BACKGROUND-RUN.md).
- Introduced unified CLI launcher script (`run`) for streamlined commands.
- Added `install_verify.sh` for environment and dependency checks.
- Launched two new scripts: `scripts/multi_source_search.py` for advanced literature search and `scripts/paper_analyzer.py` for deep paper analysis.
- Included initial test suite (`test_suit.py`) to ensure module correctness.
- Improved user onboarding and documentation for background runs and installation.
v1.0.1
**This release introduces key automation scripts for research workflow management and validation.**
- Added core scripts: check_compliance.py, generate_latex_template.py, revision_tracker.py, and verify_math_notation.py.
- Initializes structured research projects with compliance tracking and LaTeX templates.
- Supports systematic revision tracking for 6–8 paper draft rounds.
- Enables automated consistency checking of mathematical notation in LaTeX manuscripts.
- Provides compliance checks for scientific traceability and reproducibility.
v1.0.0
Initial release — A comprehensive, end-to-end management system for the computer science PhD research lifecycle.
- Supports literature surveys with multi-source search (arXiv, DBLP, ACM, IEEE) and technical thread identification.
- Tracks advisor communications and meeting action items for systematic research direction alignment.
- Enables paper writing with version control and support for iterative revision cycles (6–8 rounds).
- Provides robust experiment design, including comparison and ablation studies with automated logging.
- Includes mathematical consistency validation and full scientific traceability to meet audit and publication standards.
- Delivers standardized, compliant output directories for reproducible, well-documented academic workflows.
元数据
常见问题
phd-research-companion 是什么？
A complete PhD research lifecycle management system tailored for computer science doctoral students. Supports literature survey (arXiv/DBLP/ACM/IEEE search &... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 360 次。
如何安装 phd-research-companion？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install phd-research-companion」即可一键安装，无需额外配置。
phd-research-companion 是免费的吗？
是的，phd-research-companion 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
phd-research-companion 支持哪些平台？
phd-research-companion 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 phd-research-companion？
由 yue123161（@yue123161）开发并维护，当前版本 v1.0.2。
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