The Cure Protocol

get_expression

Read-only

SHOW WHERE A GENE IS EXPRESSED: healthy tissues and single-cell types by source (GTEx, Tabula Sapiens, proteomics), medians and units verbatim. NEXT: get_target_profile, or search_datasets for disease-tissue data.

Input Schema

Name	Required	Description
`limit`	No	Rows per source.
`source`	No	gtex, tabula_sapiens and others.
`symbol`	Yes	HGNC symbol or ENSG id.
`cellTypesOnly`	No	Cell-type rows only.

Output Schema

Name	Required	Description	Default
`data`	No	The answer. Shape depends on the tool; describe_tool documents it.
`_meta`	No	source, generatedAt, sources (per-source lastSyncedAt and ageHours), rateLimit, disclaimer.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 28, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": {},
+  "properties": {
+    "_meta": {
+      "additionalProperties": {},
+      "description": "source, generatedAt, sources (per-source lastSyncedAt and ageHours), rateLimit, disclaimer.",
+      "propertyNames": {
+        "type": "string"
+      },
+      "type": "object"
+    },
+    "data": {
+      "description": "The answer. Shape depends on the tool; describe_tool documents it."
+    }
+  },
+  "type": "object"
+}

Changed2 schema fields changedOct 24, 2026
- addedInput schema / properties / source / maxLength
```
Added value: +20000
```
- addedInput schema / properties / symbol / maxLength
```
Added value: +20000
```
AddedOct 20, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds real value beyond that: the data is restricted to healthy tissues/cell types, values are reported as medians with units verbatim, and the specific upstream sources are named — useful behavioral context for judging result comparability.

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

Conciseness5/5

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

Two sentences, front-loaded with the core capability and capped with routing guidance; every clause carries information. The ALL-CAPS emphasis on the primary action and next step is easy to scan.

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?

With an output schema present, return values needn't be described, and the description covers scope, sources, and next steps. It omits any mention of the limit/pagination behavior or what happens if the gene symbol is ambiguous (HGNC vs ENSG), which are the only remaining gaps for a 4-parameter read tool.

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 coverage is 100%, so baseline is 3, but the description adds meaning: 'single-cell types' clarifies cellTypesOnly, and naming GTEx/Tabula Sapiens/proteomics concretizes the vague 'gtex, tabula_sapiens and others' source parameter. It does not explain limit ('rows per source'), leaving that to the schema.

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?

States a specific verb and resource: shows where a gene is expressed across healthy tissues and single-cell types, with named sources (GTEx, Tabula Sapiens, proteomics). It also implicitly scopes itself against disease-tissue lookups by pointing at search_datasets, so an agent can distinguish it from siblings like get_target_profile or search_datasets.

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?

Explicit follow-up routing ('NEXT: get_target_profile, or search_datasets for disease-tissue data') and the implied exclusion of disease-tissue data give clear context for when to use it and what to call next. It stops short of stating when NOT to use this tool (e.g., if the gene symbol is unknown and resolve_identifiers is needed).

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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