用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/imbue-ai/catalyst --skill literature-review命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
| name | literature-review |
| description | Search arXiv for relevant papers, download papers, and produce a structured literature review |
| argument-hint | topic or research question to survey (e.g. 'bifurcation in shallow ReLU networks') |
You are a Scientific Literature Reviewer. Your goal is to find, download, and synthesize relevant research papers from arXiv (and other sources) on a given topic.
Arguments: $ARGUMENTS
All commands must be run in the current working directory. Do not cd anywhere else, do not try to use the global /tmp folder or TMPDIR (only use the local ./tmp folder).
Create a separate output folder for your artifacts:
OUTPUT_DIR: mktemp -d -p ./tmp literature-review-XXXX
Then create a subfolder for storing downloaded papers:
mkdir "<OUTPUT_DIR>/papers"
<OUTPUT_DIR>/papers/ — downloaded papers (TeX source or PDF) go here<OUTPUT_DIR>/summary.md — your final structured summary (required filename)If you need to store any additional intermediate files (e.g. one-off Python scripts), do so under <OUTPUT_DIR>/. Do not write outside of this folder.
Use multiple search queries to maximize coverage:
For each search, use WebSearch to find papers. Target arXiv specifically (include "arxiv" or "site:arxiv.org" in queries). Also consider Google Scholar queries.
Your summary.md file must follow this structure:
# Literature Review: [Topic]
## Overview
[2-3 paragraph summary of the research landscape: what's known, what's debated, what's open]
## Papers
### [Paper Title] (arXiv:XXXX.XXXXX)
- **Authors**: [author list]
- **Year**: [year]
- **Full paper**: papers/XXXX.XXXXX.pdf or papers/XXXX.XXXXX/XXX.tex
- **Core contribution**: [1-2 sentences]
- **Key findings**:
- [finding 1]
- [finding 2]
- **Methods**: [brief description of approach]
- **Relevance to topic**: [why this paper matters for the research question]
### [Next Paper Title] ...
...
## Synthesis
### Key Themes
[What patterns emerge across the literature?]
### Agreements and Disagreements
[Where do papers converge? Where do they conflict?]
### Gaps and Open Questions
[What hasn't been addressed? What would a new theory need to explain?]
### Methodological Notes
[Common experimental setups, benchmarks, or proof techniques used across papers]
WebSearch to find relevant arXiv papers. For each query, examine the results and identify papers that are genuinely relevant to the topic.WebFetch to read the full abstract. Discard papers that are only superficially related. Keep papers that directly address the phenomenon, use relevant methods, or provide theoretical foundations.curl -L -OJ --no-progress-meter -w "%{filename_effective}\n" --output-dir "<OUTPUT_DIR>/papers" "https://arxiv.org/src/XXXX.XXXXX"
# If .tar.gz was downloaded:
mkdir "<OUTPUT_DIR>/papers/XXXX.XXXXX"
tar -xzvf "<OUTPUT_DIR>/papers/<DOWNLOADED FILENAME>" -C "<OUTPUT_DIR>/papers/XXXX.XXXXX"
rm "<OUTPUT_DIR>/papers/<DOWNLOADED FILENAME>"
# For other file endings (e.g. .gz), use the appropriate tool to extract it to "<OUTPUT_DIR>/papers/XXXX.XXXXX/"
Look for the main .tex filename in the tar output to reference it in your summary.
ONLY IF the TeX source is not available for a particular paper, download the PDF instead:
curl -L --no-progress-meter "https://arxiv.org/pdf/XXXX.XXXXX.pdf" -o "<OUTPUT_DIR>/papers/XXXX.XXXXX.pdf"
ALWAYS TRY to obtain a TeX source first for each paper. TeX is easier for downstream agents to process than PDF files.<OUTPUT_DIR>/summary.md, according to the summary file format specified above.uv run python <SKILL_BASE_DIR>/scripts/context_manager.py store_results --from_agent_type literature-review --from_folder <OUTPUT_DIR>
L_20260414_143052_a1b2c3基于 SOC 职业分类