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get_cell_line

Get the full profile for one cancer cell line by exact name.

Returns tissue of origin, cancer type, total mutations, unique mutant peptides and
genes, data sources, Cellosaurus and DepMap model IDs, gender, category / cell
type, and the top ~15 most-mutated genes in that line, plus a link to its page.
Use after `search_cell_lines`, or when the exact name is known, for a deep dive on
one line. Returns an error field if the name is not found.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesExact cell-line name, e.g. 'MDA-MB-231', 'A549'. Use search_cell_lines first if unsure of the exact name.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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 discloses the return fields, mentions a link, and explicitly states 'Returns an error field if the name is not found'. This is thorough for a read-only lookup tool, though it doesn't explicitly state that it's a read-only operation.

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 three sentences: purpose, return details, and usage/error behavior. It is front-loaded with the primary action and contains no redundant content, though it's slightly longer than absolutely necessary.

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?

Given the tool returns a rich profile and there is no output schema or annotations, the description adequately covers return contents, error behavior, and usage context. It includes all key details to set expectations without ambiguity.

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

Parameters3/5

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

Schema description coverage is 100% with a clear description of the 'name' parameter including examples and a suggestion to use search first. The tool description adds no additional parameter semantics beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 clearly states the tool 'Get the full profile for one cancer cell line by exact name'. It lists specific return contents (tissue, cancer type, mutations, etc.) and explicitly contrasts with search_cell_lines by emphasizing 'full profile' vs. search, making its purpose unambiguous.

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?

Explicit guidance is provided: 'Use after search_cell_lines, or when the exact name is known, for a deep dive on one line.' This tells the agent when to use this tool and implicitly when not (when unsure of exact name, use search).

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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