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berntpopp
by berntpopp

Map Identifiers

map_identifiers
Read-onlyIdempotent

Map a UniProtKB accession to primary external identifiers from databases like PDB, Ensembl, GeneID, and Pfam. Optionally restrict to specific databases for targeted cross-referencing.

Instructions

Map a UniProtKB accession to its PRIMARY external identifiers: the genomic/structural/family core (PDB, AlphaFoldDB, Ensembl, RefSeq, GeneID, HGNC, KEGG, OrthoDB, Pfam, InterPro) by default. Optionally restrict to specific databases. Returns ids grouped by database plus the databases that matched and per-database counts. response_mode (default compact) returns short ids; full restores raw IRIs. For the exhaustive cross-reference set (incl. drug/disease databases like DrugBank/ChEMBL/OpenTargets) use get_protein_cross_references instead. Signature: map_identifiers(accession, databases=, response_mode=).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accessionYesUniProtKB accession, e.g. P05067 (isoforms like P05067-2 accepted).
databasesNoTarget database short names (omit for all available).
response_modeNoVerbosity: minimal | compact | standard | full (default compact).compact

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
successNo
_metaNo
error_codeNo
messageNo
retryableNo
recovery_actionNo
fieldNo
allowed_valuesNo
hintNo
accessionNo
database_countNo
countsNo
by_databaseNo
requested_databasesNo
mapped_databasesNo
unmatched_databasesNo
database_hintNo
truncated_databasesNo
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds behavior details: response mode controls verbosity, return structure (grouped by database, matched databases, counts), and explains difference between compact and full modes. Adds useful context beyond annotations.

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 front-loaded main purpose, then details, then alternative tool. It is informative but slightly verbose. Could be more concise, but every sentence adds value.

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?

Given the complexity of mapping to multiple databases, the description fully explains return format (grouped by database, counts, matched databases) and response mode behavior. Output schema exists, so return values are documented. Complete for an agent to use correctly.

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. The description adds value by providing examples (P05067, isoforms), default database list, and explanation of response_mode values. This exceeds what the schema alone provides.

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 maps a UniProtKB accession to primary external identifiers, listing specific databases and distinguishing it from the sibling tool get_protein_cross_references. The verb 'map' and resource identification are precise.

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 default behavior, optional restriction to databases, and directs to get_protein_cross_references for exhaustive cross-references. This provides clear when-to-use and when-not-to-use guidance.

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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