Smolagent Tools¶

Configuration File: smolagent_tools.json Tool Type: Local Tools Count: 2

This page contains all tools defined in the smolagent_tools.json configuration file.

Available Tools¶

advanced_literature_search_agent (Type: SmolAgentTool)¶

Advanced multi-agent literature search system. Required pipeline: (1) query_planner must produce …

advanced_literature_search_agent tool specification

Tool Information:

  • Name: advanced_literature_search_agent

  • Type: SmolAgentTool

  • Description: Advanced multi-agent literature search system. Required pipeline: (1) query_planner must produce a structured plan and immediately dispatch each sub-query to multi_database_searcher; (2) multi_database_searcher must call ToolUniverse literature tools (PubMed_search_articles, EuropePMC_search_articles, SemanticScholar_search_papers, openalex_literature_search, ArXiv_search_papers, BioRxiv_search_preprints, MedRxiv_search_preprints, Crossref_search_works, DBLP_search_publications, DOAJ_search_articles, CORE_search_papers, PMC_search_papers) and return raw results; (3) result_analyzer must deduplicate and score results; (4) literature_synthesizer must generate a structured markdown report (Executive Summary, Key Findings, Trends, Methods, Top Papers with rationale, Gaps, References). Do not skip any stage; do not answer directly without calling tools.

Parameters:

  • query (string) (required) Research query or topic to search in academic literature. The agent will automatically determine search strategy, database selection, filters, and result limits based on the query content and research domain.

Example Usage:

query = {
    "name": "advanced_literature_search_agent",
    "arguments": {
        "query": "example_value"
    }
}
result = tu.run(query)

open_deep_research_agent (Type: SmolAgentTool)¶

Research manager agent that decomposes the user task, delegates focused subtasks to domain sub‑ag…

open_deep_research_agent tool specification

Tool Information:

  • Name: open_deep_research_agent

  • Type: SmolAgentTool

  • Description: Research manager agent that decomposes the user task, delegates focused subtasks to domain sub‑agents (web researcher, synthesizer), enforces evidence use, requires numeric outputs with units, and returns a concise final answer with citations. It should: (1) draft a brief plan, (2) ask web_researcher to gather authoritative facts (URLs + extracted numbers), (3) validate consistency across sources, (4) instruct synthesizer to compute/compose the final result, and (5) output only the final, unit‑aware answer plus one short rationale line.

Parameters:

  • task (string) (required) Research query/task to execute

Example Usage:

query = {
    "name": "open_deep_research_agent",
    "arguments": {
        "task": "example_value"
    }
}
result = tu.run(query)