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CEDAR MCP Server

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term_search_from_branch

Search a BioPortal ontology branch to find standardized terms and their IRIs for a given label.

Instructions

Search BioPortal for standardized ontology terms within a specific branch.

Use this tool to find the correct standardized name and IRI for a given term label within a specific ontology branch.

Args: search_string: The term label or keyword to search for (e.g., "aspirin", "glucose") ontology_acronym: Ontology acronym to search within (e.g., "CHEBI", "HRAVS") branch_iri: IRI of the branch to restrict the search to (e.g., "http://purl.obolibrary.org/obo/CHEBI_23367")

Returns: Search results from BioPortal containing matching terms

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
branch_iriYes
search_stringYes
ontology_acronymYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

There are no annotations, so the description carries full burden. It only states that it returns search results containing matching terms, without disclosing additional behavioral traits such as pagination, rate limits, read-only nature explicitly, or what happens if no matches are found. It implies read-only through 'search' but does not explicitly confirm safety or side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description uses a clear docstring structure with purpose, Args, and Returns. It is concise and front-loaded with the primary purpose. Minor redundancy exists (e.g., re-emphasizing 'specific branch' multiple times) but overall the structure is effective and not bloated.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is a search operation with an output schema present, so return-value details are covered elsewhere. The description covers the purpose and parameters adequately. However, it lacks context on how branches are defined, potential errors, or any constraints on search behavior, leaving some gaps for a search tool with no annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It provides detailed semantics for all three parameters in the Args section, including type clarification and concrete examples (e.g., 'aspirin', 'CHEBI', 'http://purl.obolibrary.org/obo/CHEBI_23367'). This adds meaning beyond the bare schema types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches BioPortal for ontology terms within a specific branch, using a specific verb ('Search') and resource ('BioPortal... terms within a branch'). It distinguishes itself from the sibling tool 'term_search_from_ontology' by emphasizing the branch restriction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly says to use this tool to find the correct standardized name and IRI for a term label within a specific branch, giving clear context on when to use it. However, it does not mention explicit alternatives or exclusions (e.g., 'use term_search_from_ontology for whole-ontology search'), though the branch specificity effectively implies when it is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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