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rcsb_get_assemblies

Read-onlyIdempotent

Fetch biological assembly details from PDB, including composition counts and oligomeric state, for specified assembly IDs.

Instructions

Fetch biological assemblies, e.g. ["4HHB-1"] (entry-assembly).

Default fields: composition counts and oligomeric state.

Args: assembly_ids: entry-assembly, e.g. ["4HHB-1"]. Unknown IDs are returned under "not_found". fields: Optional GraphQL selection replacing the curated default (e.g. "rcsb_assembly_info.polymer_entity_instance_count"); discover/verify paths with rcsb_describe_data_object("assemblies") (see the server instructions).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNo
assembly_idsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already cover read-only, open-world, idempotence, and non-destructive behavior. The description adds valuable behavioral detail: unknown IDs are returned under 'not_found', and the default fields are specified. It also explains the 'fields' parameter's effect on the response, which goes beyond what schema annotations alone provide.

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 well-structured with a clear opening sentence, a default-fields note, and a compact list of arguments. It is slightly long due to the detailed field-path example, but every sentence contributes useful information. The front-loaded purpose makes it easy to scan.

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?

With only two parameters (one required), a read-only annotation set, and an existing output schema, the description covers all essential context: what the tool does, default behavior, parameter semantics, error handling for unknown IDs, and where to find valid field paths. No critical gaps remain.

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

Parameters5/5

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

Schema description coverage is 0%, so the description fully compensates. It explains assembly_ids with an example and the 'not_found' behavior, and fields with a concrete GraphQL path example plus a pointer to rcsb_describe_data_object for discovering valid paths. This is far more helpful than the bare schema properties.

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 'Fetch biological assemblies' – a specific verb and resource – and provides the concrete example '4HHB-1' (entry-assembly), which disambiguates it from sibling get-tools like rcsb_get_entries or rcsb_get_polymer_entities. The intent is immediately clear and distinct.

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?

The description clearly implies when to use this tool: whenever you need biological assembly data. It also provides guidance on how to customize queries with the 'fields' parameter and directs users to rcsb_describe_data_object for path discovery. It does not explicitly state when NOT to use it (e.g., for entries or polymer entities), but the resource-specific naming and examples make the context clear.

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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