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uniprot_id_mapping

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Convert identifiers between UniProt and external databases using async job submission. Handles up to 100 IDs per request.

Instructions

Map identifiers between UniProt and external databases (or between two external databases) via UniProt's ID mapping service. Submits an async job and polls it to completion server-side, so the call may take a few seconds for large batches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsYesComma-separated identifiers to map, up to 100 per call.
to_dbYesTarget database code, same code set as ``from_db``.
from_dbYesSource database code, e.g. 'UniProtKB_AC-ID', 'PDB', 'Ensembl', 'GeneID' (Entrez), or 'Gene_Name'.
response_formatNo'markdown' (default) for a human-readable report with a provenance footer, or 'json' for a machine-parseable structured payload with the same data. Any other value is rejected.markdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

The description adds the async polling behavior beyond the annotations (readOnlyHint and openWorldHint). It explains that the tool submits a job and polls to completion, which is important for the agent to understand the latency. No mention of error handling or rate limits, but the provided context is valuable.

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 two sentences long, front-loading the purpose and immediately following with the key behavioral detail (async polling). Every sentence adds value with no redundancy or fluff.

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?

The description, combined with the rich input schema and presence of an output schema, covers the essential aspects: what the tool does, how it works (async/polling), and parameter details. It could mention that mappings may be many-to-many, but the output schema likely covers return format. Overall sufficient.

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%, so the input schema already documents each parameter clearly. The tool description does not add new meaning beyond the schema. 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 maps identifiers between UniProt and external databases, using UniProt's ID mapping service. This is a specific verb-resource combination that distinguishes it from all sibling tools, none of which offer ID mapping.

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?

The description mentions the async job submission and polling behavior, which informs the agent that the call may take a few seconds. However, it does not provide explicit guidance on when to use this tool versus alternatives (e.g., uniprot_get_entry or uniprot_get_cross_refs) or when not to use it.

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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