Source profileQuality 68/100Review permissions

LazyAGI/LazyMind/skills/search/paper-search/SKILL.md

paper-search

Primary skill for searching, retrieving, and reading academic papers from arXiv.

Source repository stars
55
Declared platforms
0
Static risk flags
1
Last source update
2026-07-28
Source checked
2026-07-28

Decision brief

What it does—and where it fits

Primary skill for searching, retrieving, and reading academic papers from arXiv.

Best for

    Not for

    • Tasks that require unconfirmed production actions or broad system permissions.
    • Environments where the pinned source and install steps cannot be inspected.

    Compatibility matrix

    Platform support, with evidence labels

    PlatformStatusEvidenceWhat to check
    CodexNot declaredNo explicit evidencePortability before use
    Claude CodeNot declaredNo explicit evidencePortability before use
    CursorNot declaredNo explicit evidencePortability before use
    Gemini CLINot declaredNo explicit evidencePortability before use
    Open the compatibility checker

    Installation

    Inspect first. Install second.

    The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

    Source-detected install commandSource
    npx skills add https://github.com/LazyAGI/LazyMind --skill "skills/search/paper-search"
    Safe inspection promptEditorial

    Inspect the Agent Skill "paper-search" from https://github.com/LazyAGI/LazyMind/blob/b63cc44f8c68603bc9e802b56d8e243fef2481aa/skills/search/paper-search/SKILL.md at commit b63cc44f8c68603bc9e802b56d8e243fef2481aa. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

    Workflow

    What the source asks the agent to do

    1. 01

      Workflow & Tool Usage Guide

      Primary Method: When the user asks for papers on a topic, immediately call the native arxivsearch tool with appropriate keywords. - Example: arxivsearch(query="large language models")

      Example: arxivsearch(query="large language models")Tool Call Configuration:Read the Abstract
    2. 02

      Phase 1: Search & Discovery

      Primary Method: When the user asks for papers on a topic, immediately call the native arxivsearch tool with appropriate keywords. - Example: arxivsearch(query="large language models")

      Example: arxivsearch(query="large language models")Tool Call Configuration:Primary Method: When the user asks for papers on a topic, immediately call the native arxivsearch tool with appropriate keywords. - Example: arxivsearch(query="large language models")
    3. 03

      Phase 2: Content Retrieval

      Once you have identified target arXiv IDs, retrieve their content using urlfetch.

      Read the AbstractURL Format: https://arxiv.org/abs/Example: urlfetch(url="https://arxiv.org/abs/2402.03300")
    4. 04

      Phase 3: BibTeX Generation (Optional)

      If the user specifically asks for BibTeX citations, the native tools might not format it correctly. Use runscript to execute the BibTeX generator. - Tool Call Configuration:

      Tool Call Configuration:If the user specifically asks for BibTeX citations, the native tools might not format it correctly. Use runscript to execute the BibTeX generator. - Tool Call Configuration:

    Permission review

    Static risk signals and limitations

    Runs scripts

    medium · line 24

    The documentation asks the agent to run terminal commands or scripts.

    If the native tool malfunctions, use `run_script` to execute the fallback Python search script.

    Evidence record

    Why each signal appears

    EvidenceSourceComputedTestedEditorial
    SignalValueEvidence typeMeaning
    Quality score68/100ComputedDocumentation, specificity, maintenance, and trust rules
    Repository stars55SourceRepository attention, not individual Skill quality
    Compatibility0 platformsSourceDeclared in the catalog source record
    Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

    Pinned source

    Provenance and original SKILL.md

    Repository
    LazyAGI/LazyMind
    Skill path
    skills/search/paper-search/SKILL.md
    Commit
    b63cc44f8c68603bc9e802b56d8e243fef2481aa
    License
    Apache-2.0
    Collected
    2026-07-28
    Default branch
    main
    View the original SKILL.md

    Paper Search Skill

    Overview

    This skill provides a streamlined workflow for searching and reading academic papers from arXiv. You must default to using the system's native tools for searching and reading. Use local scripts only for specific formatting tasks (like BibTeX) or as a fallback mechanism.

    Available Tools & Priority

    1. arxiv_search (Primary): Use this first for querying papers by keyword, author, or ID.
    2. url_fetch (Primary): Use this to read abstracts and full-text HTML papers.
    3. run_script (Optional/Fallback): Use this only to generate BibTeX citations OR if arxiv_search fails to return valid results. This tool returns a dictionary.

    Workflow & Tool Usage Guide

    Phase 1: Search & Discovery

    Primary Method: When the user asks for papers on a topic, immediately call the native arxiv_search tool with appropriate keywords.

    • Example: arxiv_search(query="large language models")

    Fallback Method (If arxiv_search fails or returns empty/errors): If the native tool malfunctions, use run_script to execute the fallback Python search script.

    • Tool Call Configuration:
      {
        "name": "paper-search",
        "rel_path": "scripts/search_arxiv.py",
        "args": ["<your_search_query>"]
      }
      

    Phase 2: Content Retrieval

    Once you have identified target arXiv IDs, retrieve their content using url_fetch.

    1. Read the Abstract
    • URL Format: https://arxiv.org/abs/<arxiv_id>
    • Example: url_fetch(url="https://arxiv.org/abs/2402.03300")
    1. Read the Full Paper (HTML Version) To read the actual paper content (Methodology, Experiments, etc.), fetch the HTML version (preserves text and tables better than PDFs):
    • URL Format: https://ar5iv.labs.arxiv.org/html/<arxiv_id>
    • Example: url_fetch(url="https://ar5iv.labs.arxiv.org/html/2402.03300")

    Phase 3: BibTeX Generation (Optional)

    If the user specifically asks for BibTeX citations, the native tools might not format it correctly. Use run_script to execute the BibTeX generator.

    • Tool Call Configuration:
      {
        "name": "paper-search",
        "rel_path": "scripts/get_bibtex.py",
        "args": ["<arxiv_id>"]
      }
      

    Example <arxiv_id>: 2402.03300

    Constraints & Rules

    • Tool Priority: Always attempt arxiv_search before resorting to scripts/search_arxiv.py.
    • Arguments Format: When using run_script, the args parameter MUST be a List of strings (List[str]).
    • ID Versioning: 2402.03300 resolves to the latest version. Use unversioned IDs for lookups unless the user specifically requests an older version.

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