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identify_spatial_domains

Destructive

Identify spatial domains and tissue architecture in spatial transcriptomics data. Choose from SpaGCN, BANKSY, STAGATE, GraphST, and other clustering methods for your analysis.

Instructions

Identify spatial domains and tissue architecture.

Args:
    data_id: Dataset ID
    params: Spatial domain parameters (method, n_domains, resolution, etc.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNo
data_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
methodYes
data_idYes
warningsNoNon-fatal conditions that may affect result interpretation.
n_domainsYes
domain_keyYes
domain_countsYes
embeddings_keyNo
refined_domain_keyNo
Behavior3/5

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

Annotations already declare destructiveHint=true and readOnlyHint=false, so the agent knows this is a mutating operation. The description itself adds no new behavioral context, such as what data is modified or whether results are stored back to the dataset. It does not contradict the annotations, but also does not supplement them.

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 is concise and front-loaded with the purpose statement. The 'Args' section is brief but somewhat redundant with the schema. No wasted words, but it could be slightly more informative without losing conciseness.

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

Completeness2/5

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

This is a complex tool with many methods and nested parameters, plus a destructive annotation. The description is too sparse, lacking an overview of supported algorithms, expected runtime, or side effects. The rich schema covers parameter details, but the high-level context is missing for an agent to fully anticipate behavior.

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

Parameters2/5

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

The description lists only 'data_id: Dataset ID' and 'params: Spatial domain parameters (method, n_domains, resolution, etc.)'. It gives minimal meaning and does not explain required status, defaults, or method selection. With top-level schema description coverage at 0%, the description barely compensates, though the nested schema is detailed.

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

Purpose4/5

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

The description states 'Identify spatial domains and tissue architecture,' which is a specific verb+resource. It clearly distinguishes from siblings such as analyze_spatial_statistics or find_spatial_genes, which target different analyses. However, 'tissue architecture' is a broad term, and the description could more explicitly define the tool's output or scope.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It lacks any mention of prerequisites, recommended scenarios, or how it compares to related spatial-analysis sibling tools. No exclusions or alternative tool references are given.

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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