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batch_resolve_genes

Resolve lists of gene symbols, aliases, or IDs in batch with concurrency control, returning success rates and mapped biological entities.

Instructions

Resolve a list of gene identifiers/aliases in batch with concurrency control and performance metrics.

Args: queries: List of gene symbols or aliases (e.g. ["TP53", "HER2", "EGFR", "7157", "P04637"]). taxon_id: NCBI Taxonomy ID (default: 9606 for human). concurrency: Maximum concurrent requests (default: 10).

Returns: JSON string containing the batch resolution summary, success rate, and resolved entities.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`queries`	Yes
`taxon_id`	No
`concurrency`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.7.0Sep 30, 2026
- addedInput schema / properties / concurrency
```
Added value: +{
+  "default": 10,
+  "title": "Concurrency",
+  "type": "integer"
+}
```
First observedv0.1.0Sep 27, 2026

TDQS

A3.9/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does add useful behavioral context — concurrency control, performance metrics, a success rate in the return — which hints at partial-failure semantics. However it says nothing about rate limits, required auth, or how failed individual queries are reported.

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 one-line summary is front-loaded and the Args block is tight. The Returns section is partly redundant given an output schema exists, but it is short and states the summary/success-rate/resolved-entity shape.

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?

For a 3-parameter tool with an output schema, the description covers inputs thoroughly and touches outcomes. The remaining gap is batch-specific failure behavior (what happens when some identifiers do not resolve), which is not addressed.

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, and it largely does: it documents all three parameters, explains taxon_id as an NCBI Taxonomy ID with the human default, and gives concrete query examples spanning symbols, aliases, Entrez IDs (7157) and UniProt IDs (P04637) — meaning the schema does not convey.

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 ('resolve a list of gene identifiers/aliases in batch'), naming the batch scope that separates it from the sibling resolve_gene. An agent can route between the two without opening either schema.

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

Usage Guidelines3/5

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

Usage is implied by 'in batch' and the concurrency parameter, but there is no explicit statement of when to prefer this over resolve_gene or the other resolution siblings, nor any prerequisites. The agent must infer the batch-vs-single split.

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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