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Exa Research Papers

作者 Mario Karras · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
235
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1
当前安装
1
版本数
在 OpenClaw 中安装
/install abm-exa-research-papers
功能描述
Find academic papers, studies, and research on any topic using Exa's research paper category search. Use when the user mentions 'find papers,' 'research pape...
使用说明 (SKILL.md)

Exa Research Papers

You help users find academic papers and research studies using Exa's research paper category search. Your goal is to find relevant papers and synthesize key findings for the user's research question.

Before Starting

Check for product marketing context first: If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Understand what the user needs (ask if not provided):

  1. Research topic -- what subject or question are they researching?
  2. Specific questions -- what do they want to learn or prove?
  3. Field/discipline -- if known (e.g., computer science, psychology, economics)
  4. Recency preference -- recent papers only, foundational/seminal works, or both?

Workflow

Step 1: Search for Papers

Run via exec:

exa.js search --query "[research topic]" --category "research paper" --num-results 10

For recent papers only, add a date filter:

exa.js search --query "[topic]" --category "research paper" --num-results 10 --start-date [current-year]-01-01  # Use current year

Step 2: Refine the Search

If results are too broad, narrow with specific terms:

exa.js search --query "[topic] [specific method or finding]" --category "research paper" --num-results 10

Step 3: Fetch Paper Content

For the most relevant results, fetch content to read abstracts and key sections:

exa.js contents --ids "[id1],[id2]" --text --highlights

Use the IDs returned from the search results.

Step 4: Synthesize Key Findings

Summarize the papers in the context of the user's research question. Highlight agreements and disagreements across papers.


Dry Run

To preview the request without making an API call:

exa.js search --query "[topic]" --category "research paper" --dry-run

Output Format

For each paper found:

  • Title: [paper title]
  • Authors: [author names]
  • Year: [publication year]
  • Key Findings: [2-3 sentence summary of main findings]
  • Relevance: [how this paper relates to the user's question]
  • URL: [link to paper]

After listing papers, provide a Synthesis section:

  • Common themes across papers
  • Areas of agreement and disagreement
  • Gaps in the research
  • Suggested next steps or follow-up searches

Tips

  • Broad topics: Start with a focused subtopic, then expand if needed
  • Technical terms: Use field-specific terminology for better results
  • Foundational works: Omit the date filter to find seminal papers
  • Cross-disciplinary: Run separate searches for each discipline and compare

Related Skills

  • exa-company-research: Research companies, not academic topics
  • content-strategy: Turn research findings into content plans
安全使用建议
Do not enable this skill without clarifying a few things. Ask the publisher: (1) Where does exa.js come from? Provide an install spec or canonical source (GitHub release, npm package with homepage, or packaged binary). (2) Does exa.js require API keys or other credentials? If so, the skill should declare them in requires.env and explain scope/usage. (3) Why does the skill read .agents/product-marketing-context.md and what sensitive data might that file contain? If you permit file reading, limit the skill's workspace access or sanitize the file first. If you must test, run the agent in a restricted sandbox and verify the exa.js binary's source and contents before allowing exec. If the publisher cannot answer these questions or provide an install/credential spec, treat the skill as untrusted.
功能分析
Type: OpenClaw Skill Name: abm-exa-research-papers Version: 1.0.0 The skill bundle provides instructions for an AI agent to perform academic research using the exa.js CLI tool. It follows a standard workflow of searching, fetching, and synthesizing research papers. No malicious patterns, data exfiltration, or unauthorized execution were found in SKILL.md or _meta.json.
能力评估
Purpose & Capability
The SKILL.md explicitly instructs the agent to run the exa.js CLI (exa.js search / exa.js contents), which is central to the skill's functionality; however, the skill metadata declares no required binaries and provides no install specification. That inconsistency means the skill either assumes a binary will already exist (unstated requirement) or is missing an install step. Additionally, the instructions reference reading .agents/product-marketing-context.md (or .claude/...), which is outside the stated 'find papers' purpose unless marketing context is deliberately needed — this file access is not declared in required config paths.
Instruction Scope
Runtime instructions direct exec of a local binary (exa.js) and instruct the agent to read product-marketing-context files if present. exec-style commands can run arbitrary code; the SKILL.md gives no guardrails, no verification of the binary's origin, and no explicit limit on what local files can be read. The instruction also permits fetching paper contents (which may require API credentials in practice) but those credentials are not declared.
Install Mechanism
There is no install spec (instruction-only), which is low risk if the agent only runs safe, declared commands. Here, however, the skill depends on an external CLI (exa.js) yet provides no install instructions or trusted source for that binary. That omission raises risk: users may run an unknown exa.js obtained from an untrusted source, or the agent may fail or call an unexpected binary on PATH.
Credentials
The skill declares no required environment variables or credentials, but the described workflow (searching and fetching paper contents via exa.js) commonly requires API keys or service credentials. The SKILL.md also asks the agent to read product-marketing-context files from the workspace, which might contain sensitive information. The lack of declared environment/credential requirements is disproportionate to the operations the skill performs.
Persistence & Privilege
The skill does not request permanent presence (always: false) and does not declare actions that modify other skills or system-wide settings. It appears to be user-invocable and not forcibly injected into all agent runs.
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 abm-exa-research-papers
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /abm-exa-research-papers 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
v1.0.0
Initial release of exa-research-papers skill: - Enables searching for academic and scientific papers by topic using Exa's research paper category. - Guides users through understanding research needs, refining queries, and synthesizing findings. - Provides clear workflow for searching, narrowing results, fetching paper content, and summarizing insights. - Includes structured output format with paper details and a synthesis section. - Specifies when to use this skill versus related skills for company or market research.
元数据
Slug abm-exa-research-papers
版本 1.0.0
许可证 MIT-0
累计安装 1
当前安装数 1
历史版本数 1
常见问题

Exa Research Papers 是什么?

Find academic papers, studies, and research on any topic using Exa's research paper category search. Use when the user mentions 'find papers,' 'research pape... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 235 次。

如何安装 Exa Research Papers?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install abm-exa-research-papers」即可一键安装,无需额外配置。

Exa Research Papers 是免费的吗?

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

Exa Research Papers 支持哪些平台?

Exa Research Papers 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 Exa Research Papers?

由 Mario Karras(@mariokarras)开发并维护,当前版本 v1.0.0。

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