median_expressionMedian expression across tissues for a gene (TPM).
| Name | Required | Description | Default |
|---|---|---|---|
| gene | Yes | Gene symbol (e.g. "TP53") or versioned Gencode id (e.g. "ENSG00000141510.16"). Symbols are resolved automatically. | |
| datasetId | No | gtex_v8 (default) | gtex_v10 |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / datasetIdAdded value: +{
+ "description": "gtex_v8 (default) | gtex_v10",
+ "type": "string"
+}Input schema / properties / gene / descriptionPrevious value: -"Gencode id or symbol."New value: +"Gene symbol (e.g. \"TP53\") or versioned Gencode id (e.g. \"ENSG00000141510.16\"). Symbols are resolved automatically."Input schema / examplesAdded value: +[
+ {
+ "gene": "TP53"
+ },
+ {
+ "gene": "ENSG00000141510.16"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "description": "Median expression values across tissues for a gene in TPM",
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint as false. The description adds behavioral context (aggregated median across tissues, TPM units) that goes beyond annotations, aligning well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence with no wasted words. It conveys the core purpose immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the presence of an output schema, and full parameter descriptions, the description is complete. It covers the essential information needed to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for both parameters, so the baseline is 3. The tool description does not add extra parameter details beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns median TPM expression across tissues for a gene. It is specific and understandable, but does not explicitly differentiate from sibling tools like 'single_tissue_eqtls' or 'top_expressed_genes', though the function is distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not specify when to use this tool over alternatives, nor does it mention any prerequisites or context.
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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