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togoid_getRelation

Check if a specific ID conversion route exists between source and target databases, and retrieve details including forward/reverse relationship labels and description.

Instructions

Check if a specific ID conversion route exists and get its details.

Use this to verify that a particular source→target conversion is available before calling convertId. Also reveals the nature of the relationship (e.g., "encoded by", "has structure", "is target of").

Args: source: Source database key (e.g., 'uniprot', 'ncbigene', 'chembl_target') target: Target database key (e.g., 'pdb', 'ensembl_gene', 'hgnc')

Returns: JSON string: a bare array of relationship objects with: - forward: relationship label from source to target - reverse: relationship label from target to source - description: explanation of the link

Example: >>> getRelation('ncbigene', 'uniprot') # Shows: ncbigene → uniprot via "encoded by" relationship

>>> getRelation('uniprot', 'pdb')
# Shows: uniprot → pdb via "has structure" relationship

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYes
targetYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description carries full burden. It describes the return format and relationship labels, but does not disclose potential side effects, auth requirements, or rate limits. Behavior is consistent with tool function.

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?

Well-structured with sections: intro, usage, args, returns, examples. Front-loaded with purpose. Slightly lengthy due to example redundancy, but overall concise for the information provided.

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

Completeness4/5

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

Covers purpose, usage, parameter semantics, and return format. Missing error handling or behavior when route does not exist. Output schema exists, so return details are supplemented.

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

Parameters5/5

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

Schema description coverage is 0%, but description adds significant value with examples for source ('uniprot', 'ncbigene', 'chembl_target') and target ('pdb', 'ensembl_gene', 'hgnc'), clarifying expected keys.

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?

Description uses a specific verb ('Check') and identifies the resource ('ID conversion route'). It distinguishes from sibling tools like togoid_convertId and togoid_getAllRelation by focusing on route existence and relationship details.

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?

Explicitly states when to use: 'verify that a particular source→target conversion is available before calling convertId.' It also explains what the tool reveals (relationship nature). Lacks explicit when-not-to-use statements but context is clear.

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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