Agentic Tools

Configuration File: agentic_tools.json Tool Type: Local Tools Count: 25

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

Available Tools

AdvancedCodeQualityAnalyzer (Type: AgenticTool)

Performs deep analysis of code quality including complexity, security, performance, and maintaina…

AdvancedCodeQualityAnalyzer tool specification

Tool Information:

• Name: AdvancedCodeQualityAnalyzer

• Type: AgenticTool

• Description: Performs deep analysis of code quality including complexity, security, performance, and maintainability metrics with domain-specific expertise

Parameters:

• source_code (string) (required) The source code to analyze for quality assessment

• language (string) (optional) Programming language (python, javascript, etc.)

• analysis_depth (string) (optional) Level of analysis depth to perform

• domain_context (string) (optional) Domain context for specialized analysis (e.g., bioinformatics, web development)

Example Usage:

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

DataAnalysisValidityReviewer (Type: AgenticTool)

Checks statistical choices, assumption testing, and reporting transparency.

DataAnalysisValidityReviewer tool specification

Tool Information:

• Name: DataAnalysisValidityReviewer

• Type: AgenticTool

• Description: Checks statistical choices, assumption testing, and reporting transparency.

Parameters:

• analysis_section (string) (required) No description

Example Usage:

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

DescriptionAnalyzer (Type: AgenticTool)

Analyzes a tool’s original description and the results of multiple test cases, then suggests an i…

DescriptionAnalyzer tool specification

Tool Information:

• Name: DescriptionAnalyzer

• Type: AgenticTool

• Description: Analyzes a tool’s original description and the results of multiple test cases, then suggests an improved description that is more accurate, comprehensive, and user-friendly. Optionally provides a rationale for the changes.

Parameters:

• original_description (string) (required) The original description of the tool.

• test_results (string) (required) A JSON string containing a list of test case input/output pairs.

Example Usage:

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

DescriptionQualityEvaluator (Type: AgenticTool)

Evaluates the quality of tool descriptions and parameter descriptions, providing a score and spec…

DescriptionQualityEvaluator tool specification

Tool Information:

• Name: DescriptionQualityEvaluator

• Type: AgenticTool

• Description: Evaluates the quality of tool descriptions and parameter descriptions, providing a score and specific feedback for improvements.

Parameters:

• tool_description (string) (required) The tool description to evaluate.

• parameter_descriptions (string) (required) JSON string of parameter names and their descriptions.

• test_results (string) (required) JSON string containing test case results.

Example Usage:

query = {
    "name": "DescriptionQualityEvaluator",
    "arguments": {
        "tool_description": "example_value",
        "parameter_descriptions": "example_value",
        "test_results": "example_value"
    }
}
result = tu.run(query)

DomainExpertValidator (Type: AgenticTool)

Provides domain-specific validation and expert recommendations for tools with deep expertise acro…

DomainExpertValidator tool specification

Tool Information:

• Name: DomainExpertValidator

• Type: AgenticTool

• Description: Provides domain-specific validation and expert recommendations for tools with deep expertise across scientific and technical domains

Parameters:

• tool_config (string) (required) JSON string of tool configuration to validate

• domain (string) (required) Domain expertise area for validation

• validation_aspects (string) (optional) JSON array string of specific aspects to validate

• implementation_code (string) (optional) Implementation code to validate (optional)

Example Usage:

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

EthicalComplianceReviewer (Type: AgenticTool)

Checks adherence to ethical standards and disclosure practices.

EthicalComplianceReviewer tool specification

Tool Information:

• Name: EthicalComplianceReviewer

• Type: AgenticTool

• Description: Checks adherence to ethical standards and disclosure practices.

Parameters:

• ethics_section (string) (required) No description

Example Usage:

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

ExperimentalDesignScorer (Type: AgenticTool)

Assesses a proposed experimental design by assigning scores and structured feedback on hypothesis…

ExperimentalDesignScorer tool specification

Tool Information:

• Name: ExperimentalDesignScorer

• Type: AgenticTool

• Description: Assesses a proposed experimental design by assigning scores and structured feedback on hypothesis clarity, variable definitions, sample size, controls, randomization, measurement methods, statistical analysis, bias mitigation, ethical considerations, and overall feasibility.

Parameters:

• hypothesis (string) (required) A clear statement of the research hypothesis to be tested.

• design_description (string) (required) A detailed description of the proposed experimental design, including variables, methods, sample details, and planned analyses.

Example Usage:

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

HypothesisGenerator (Type: AgenticTool)

Generates research hypotheses based on provided background context, domain, and desired format. U…

HypothesisGenerator tool specification

Tool Information:

• Name: HypothesisGenerator

• Type: AgenticTool

• Description: Generates research hypotheses based on provided background context, domain, and desired format. Uses AI to propose novel, testable hypotheses for scientific exploration.

Parameters:

• context (string) (required) Background information, observations, or data description from which to derive hypotheses.

• domain (string) (required) Field of study or research area (e.g., ‘neuroscience’, ‘ecology’, ‘materials science’).

• number_of_hypotheses (string) (required) Number of hypotheses to generate (e.g., ‘3’, ‘5’).

• hypothesis_format (string) (optional) Optional directive on how to structure each hypothesis. Choose from one of the following formats:

1. If–Then Statements: “If [independent variable condition], then [expected outcome].”

2. Null and Alternative (Statistical): • H₀ (Null): “There is no difference/effect/association between X and Y.” • H₁ (Alt): “There is a difference/effect/association between X and Y.”

3. Associative (Correlation-Focused): “There is a relationship/association between [Variable A] and [Variable B].”

4. Directional (Non-If–Then): “Increasing/decreasing [Variable A] will lead to [directional change] in [Variable B].”

5. Comparative (Group Comparison): “Group A will show higher/lower [dependent measure] compared to Group B under [condition].”

6. Mechanistic: “Because [mechanism or process], [Variable A] will cause [Variable B].”

7. Descriptive (Exploratory/Pattern-Oriented): “Population X exhibits pattern Y in context Z.”

If omitted, defaults to concise declarative sentences.

Example Usage:

query = {
    "name": "HypothesisGenerator",
    "arguments": {
        "context": "example_value",
        "domain": "example_value",
        "number_of_hypotheses": "example_value"
    }
}
result = tu.run(query)

LabelGenerator (Type: AgenticTool)

Generates relevant keyword labels for tools based on their name, description, parameters, and cat…

LabelGenerator tool specification

Tool Information:

• Name: LabelGenerator

• Type: AgenticTool

• Description: Generates relevant keyword labels for tools based on their name, description, parameters, and category. Creates a comprehensive list of tags for tool discovery and categorization.

Parameters:

• tool_name (string) (required) The name of the tool

• tool_description (string) (required) Detailed description of what the tool does

• tool_parameters (string) (required) JSON string describing the tool’s input parameters and their types

• category (string) (required) The general category or domain the tool belongs to

• existing_labels (string) (optional) JSON array string of existing labels to consider reusing (optional)

Example Usage:

query = {
    "name": "LabelGenerator",
    "arguments": {
        "tool_name": "example_value",
        "tool_description": "example_value",
        "tool_parameters": "example_value",
        "category": "example_value"
    }
}
result = tu.run(query)

LiteratureContextReviewer (Type: AgenticTool)

Reviews coverage, relevance, and critical synthesis of prior scholarship.

LiteratureContextReviewer tool specification

Tool Information:

• Name: LiteratureContextReviewer

• Type: AgenticTool

• Description: Reviews coverage, relevance, and critical synthesis of prior scholarship.

Parameters:

• paper_title (string) (required) No description

• literature_review (string) (required) Full literature-review text

Example Usage:

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

MedicalLiteratureReviewer (Type: AgenticTool)

Conducts systematic reviews of medical literature on specific topics. Synthesizes findings from m…

MedicalLiteratureReviewer tool specification

Tool Information:

• Name: MedicalLiteratureReviewer

• Type: AgenticTool

• Description: Conducts systematic reviews of medical literature on specific topics. Synthesizes findings from multiple studies and provides evidence-based conclusions with structured analysis and quality assessment.

Parameters:

• research_topic (string) (required) The specific medical/research topic for literature review (e.g., ‘efficacy of drug X in treating condition Y’).

• literature_content (string) (required) The literature content, abstracts, full studies, or research papers to review and synthesize.

• focus_area (string) (required) Primary focus area for the review (e.g., ‘therapeutic efficacy’, ‘safety profile’, ‘diagnostic accuracy’, ‘biomarker validation’).

• study_types (string) (required) Types of studies to prioritize in the analysis (e.g., ‘randomized controlled trials’, ‘meta-analyses’, ‘cohort studies’, ‘case-control studies’).

• quality_level (string) (required) Minimum evidence quality level to include (e.g., ‘high quality only’, ‘moderate and above’, ‘all available evidence’).

• review_scope (string) (required) Scope of the review (e.g., ‘comprehensive systematic review’, ‘rapid review’, ‘scoping review’, ‘narrative review’).

Example Usage:

query = {
    "name": "MedicalLiteratureReviewer",
    "arguments": {
        "research_topic": "example_value",
        "literature_content": "example_value",
        "focus_area": "example_value",
        "study_types": "example_value",
        "quality_level": "example_value",
        "review_scope": "example_value"
    }
}
result = tu.run(query)

MedicalTermNormalizer (Type: AgenticTool)

Identifies and corrects misspelled drug or disease names, returning a list of plausible standardi…

MedicalTermNormalizer tool specification

Tool Information:

• Name: MedicalTermNormalizer

• Type: AgenticTool

• Description: Identifies and corrects misspelled drug or disease names, returning a list of plausible standardized terms.

Parameters:

• raw_terms (string) (required) A comma- or whitespace-separated string containing one misspelled drug or disease name.

Example Usage:

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

MethodologyRigorReviewer (Type: AgenticTool)

Evaluates design appropriateness, sampling, and procedural transparency.

MethodologyRigorReviewer tool specification

Tool Information:

• Name: MethodologyRigorReviewer

• Type: AgenticTool

• Description: Evaluates design appropriateness, sampling, and procedural transparency.

Parameters:

• methods_section (string) (required) Full Methods text

Example Usage:

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

NoveltySignificanceReviewer (Type: AgenticTool)

Provides a structured peer-review of the work’s originality and potential impact.

NoveltySignificanceReviewer tool specification

Tool Information:

• Name: NoveltySignificanceReviewer

• Type: AgenticTool

• Description: Provides a structured peer-review of the work’s originality and potential impact.

Parameters:

• paper_title (string) (required) Manuscript title

• abstract (string) (required) Manuscript abstract

• manuscript_text (string) (required) Full manuscript text

Example Usage:

query = {
    "name": "NoveltySignificanceReviewer",
    "arguments": {
        "paper_title": "example_value",
        "abstract": "example_value",
        "manuscript_text": "example_value"
    }
}
result = tu.run(query)

ProtocolOptimizer (Type: AgenticTool)

Reviews an initial protocol and delivers targeted revisions that improve clarity, feasibility, ri…

ProtocolOptimizer tool specification

Tool Information:

• Name: ProtocolOptimizer

• Type: AgenticTool

• Description: Reviews an initial protocol and delivers targeted revisions that improve clarity, feasibility, risk-management, and evaluation rigor.

Parameters:

• initial_protocol (string) (required) No description

Example Usage:

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

QuestionRephraser (Type: AgenticTool)

Generates three distinct paraphrases of a given question while ensuring answer options remain val…

QuestionRephraser tool specification

Tool Information:

• Name: QuestionRephraser

• Type: AgenticTool

• Description: Generates three distinct paraphrases of a given question while ensuring answer options remain valid and applicable.

Parameters:

• question (string) (required) The original question text to be rephrased

• options (string) (optional) Answer options (e.g., multiple choice options) that should remain valid for the rephrased questions. Leave empty if no options are provided.

Example Usage:

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

ReproducibilityTransparencyReviewer (Type: AgenticTool)

Evaluates data, code, and protocol availability for replication.

ReproducibilityTransparencyReviewer tool specification

Tool Information:

• Name: ReproducibilityTransparencyReviewer

• Type: AgenticTool

• Description: Evaluates data, code, and protocol availability for replication.

Parameters:

• availability_statement (string) (required) No description

Example Usage:

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

ResultsInterpretationReviewer (Type: AgenticTool)

Judges whether conclusions are data-justified and limitations addressed.

ResultsInterpretationReviewer tool specification

Tool Information:

• Name: ResultsInterpretationReviewer

• Type: AgenticTool

• Description: Judges whether conclusions are data-justified and limitations addressed.

Parameters:

• results_section (string) (required) No description

• discussion_section (string) (required) No description

Example Usage:

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

ScientificTextSummarizer (Type: AgenticTool)

Summarizes biomedical research texts, abstracts, or papers with specified length and focus areas….

ScientificTextSummarizer tool specification

Tool Information:

• Name: ScientificTextSummarizer

• Type: AgenticTool

• Description: Summarizes biomedical research texts, abstracts, or papers with specified length and focus areas. Uses AI to extract key findings, methodology, and conclusions from complex biomedical literature.

Parameters:

• text (string) (required) The biomedical text, abstract, or paper content to be summarized.

• summary_length (string) (required) Desired length of summary (e.g., ‘50’, ‘100’, ‘200 words’).

• focus_area (string) (required) What to focus on in the summary (e.g., ‘methodology’, ‘results’, ‘clinical implications’, ‘drug interactions’).

Example Usage:

query = {
    "name": "ScientificTextSummarizer",
    "arguments": {
        "text": "example_value",
        "summary_length": "example_value",
        "focus_area": "example_value"
    }
}
result = tu.run(query)

ToolMetadataGenerator (Type: AgenticTool)

Generates a JSON structure with the metadata of a tool in ToolUniverse, given the JSON configurat…

ToolMetadataGenerator tool specification

Tool Information:

• Name: ToolMetadataGenerator

• Type: AgenticTool

• Description: Generates a JSON structure with the metadata of a tool in ToolUniverse, given the JSON configuration of the tool.

Parameters:

• tool_config (string) (required) JSON string of the tool configuration to extract metadata from

• tool_type_mappings (object) (optional) A mapping from a simplified toolType to a list of tool_config.type that fall under the toolType (e.g., {‘Databases’: [‘XMLTool’]})

Example Usage:

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

ToolMetadataStandardizer (Type: AgenticTool)

Standardizes and groups semantically equivalent metadata strings (e.g., sources, tags) into canon…

ToolMetadataStandardizer tool specification

Tool Information:

• Name: ToolMetadataStandardizer

• Type: AgenticTool

• Description: Standardizes and groups semantically equivalent metadata strings (e.g., sources, tags) into canonical forms for consistent downstream usage.

Parameters:

• metadata_list (array) (required) List of raw metadata strings (e.g., sources, tags) to standardize and group.

• limit (integer) (optional) If provided, the maximum number of canonical strings to return. The LLM will group terms more aggressively to meet this limit, ensuring all raw strings are mapped.

Example Usage:

query = {
    "name": "ToolMetadataStandardizer",
    "arguments": {
        "metadata_list": ["item1", "item2"]
    }
}
result = tu.run(query)

ToolQualityEvaluator (Type: AgenticTool)

Evaluates the quality of tool configurations and implementations. Provides detailed scoring and f…

ToolQualityEvaluator tool specification

Tool Information:

• Name: ToolQualityEvaluator

• Type: AgenticTool

• Description: Evaluates the quality of tool configurations and implementations. Provides detailed scoring and feedback for improvement.

Parameters:

• tool_config (string) (required) JSON string of the tool configuration

• test_cases (string) (required) JSON string of test cases

• evaluation_aspects (array) (required) Aspects to evaluate (functionality, usability, completeness, best_practices)

Example Usage:

query = {
    "name": "ToolQualityEvaluator",
    "arguments": {
        "tool_config": "example_value",
        "test_cases": "example_value",
        "evaluation_aspects": ["item1", "item2"]
    }
}
result = tu.run(query)

ToolRelationshipDetector (Type: AgenticTool)

Analyzes a primary tool against a list of other tools to identify meaningful, directional data fl…

ToolRelationshipDetector tool specification

Tool Information:

• Name: ToolRelationshipDetector

• Type: AgenticTool

• Description: Analyzes a primary tool against a list of other tools to identify meaningful, directional data flow compatibilities for scientific workflows. Returns a list of compatible pairs with direction and rationale.

Parameters:

• tool_a (string) (required) JSON string for the primary tool configuration (Tool A).

• other_tools (string) (required) JSON string of a list of other tool configurations to compare against Tool A.

Example Usage:

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

WritingPresentationReviewer (Type: AgenticTool)

Assesses clarity, organization, grammar, and visual presentation quality.

WritingPresentationReviewer tool specification

Tool Information:

• Name: WritingPresentationReviewer

• Type: AgenticTool

• Description: Assesses clarity, organization, grammar, and visual presentation quality.

Parameters:

• manuscript_text (string) (required) No description

Example Usage:

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

call_agentic_human (Type: AgenticTool)

Produces a concise, practical answer that emulates how a well-informed human would respond to the…

call_agentic_human tool specification

Tool Information:

• Name: call_agentic_human

• Type: AgenticTool

• Description: Produces a concise, practical answer that emulates how a well-informed human would respond to the question.

Parameters:

• question (string) (required) The user’s question to be answered in a human-like manner.

Example Usage:

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

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