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can-immune

by io.github.sanjaysgk
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search_genes

Find genes by symbol or full name, ranked by how mutated they are.

Matches the gene symbol OR the full gene name (partial, case-insensitive) and
returns each hit with its total mutation count, unique mutant-peptide count,
sample count, and UniProt accession. Use it to locate a gene before calling
`get_gene`, or to rank a set of genes by mutation burden. Results are ordered by
mutation count (most mutated first).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax rows to return (1-100). Default 20.
queryYesGene symbol or part of a gene name, e.g. 'TP53', 'BRAF', or 'kinase'. Case-insensitive, partial matches allowed.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description discloses key behaviors: matching is partial and case-insensitive, results contain four specific fields, and ordering is by mutation count. It doesn't cover edge cases like empty results or authentication, but it provides a solid behavioral contract for a search tool.

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?

The description is three well-organized sentences: purpose, matching/return details, and usage guidance. It is front-loaded and every clause adds value, without redundancy beyond reinforcing the schema.

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

Completeness5/5

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

For a simple 2-parameter search tool with no output schema, the description sufficiently explains return values and ordering. It also provides usage context and distinguishes from related tools, making it self-contained.

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?

The input schema already provides 100% coverage for `query` and `limit`. The description adds context about result ranking and return fields, which helps interpret the query parameter, but doesn't introduce new parameter syntax. This earns a slight uplift from the baseline.

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?

The description opens with a specific verb+resource ('Find genes by symbol or full name') and adds the ranking criterion ('ranked by how mutated they are'). It also distinguishes itself from the sibling `get_gene` by positioning itself as a precursor ('before calling get_gene').

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

Usage Guidelines5/5

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

Explicitly states two use cases: locating a gene before `get_gene` and ranking genes by mutation burden. This gives clear guidance for when to choose this tool over the sibling tool. It names the alternative tool explicitly, which satisfies the 'alternatives' criterion.

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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