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by com.seqbench

Submit a batch gene/protein ID mapping job

id_map_submit
Read-onlyIdempotent

Submit up to 1000 ids to UniProt's ID mapping service for a single confirmed-safe hop (e.g. Gene_Name -> UniProtKB-Swiss-Prot, or UniProtKB_AC-ID -> Ensembl/GeneID/RefSeq_Protein/Gene_Name). Returns a jobId immediately — poll it with id_map_poll.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesTarget id type. Supported single hops: Gene_Name/Ensembl/GeneID/RefSeq_Protein -> "UniProtKB-Swiss-Prot" (the only direct target for these), or "UniProtKB_AC-ID" -> Ensembl/GeneID/RefSeq_Protein/Gene_Name. Any other pair is rejected — chain two of these hops instead.
idsYesThe ids to map, up to 1000 (e.g. gene symbols, UniProt accessions, Ensembl gene IDs, Entrez GeneIDs, or RefSeq protein accessions, depending on "from").
fromYesSource id type: "Gene_Name", "Ensembl", "GeneID", "RefSeq_Protein", or "UniProtKB_AC-ID". UniProt's mapping graph is hub-and-spoke — see the "to" note.
taxIdNoNCBI taxonomy id to disambiguate a gene symbol (only used when from="Gene_Name"). Defaults to human (9606) if omitted.

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already provide readOnlyHint and idempotentHint. The description adds value by specifying the 1000 ID limit and that it returns a jobId immediately, but does not add significant behavioral context beyond what annotations imply. No contradiction with annotations.

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 concise sentences, front-loaded with the core action and examples, and includes the important note about polling. No wasted words.

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 submission tool, the description is complete: it explains what it does, the limit, the return value (jobId), and how to get results (poll id_map_poll). The schema covers all parameter details, and the sibling tool for polling is referenced.

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 very detailed parameter descriptions. The description adds some examples of valid hops but does not significantly enhance parameter understanding beyond the schema. Baseline 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 submits up to 1000 IDs to UniProt's ID mapping service for a single confirmed-safe hop, with concrete examples like Gene_Name -> UniProtKB-Swiss-Prot. It distinguishes itself from the sibling id_map_poll by stating it returns a jobId to poll.

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 explains when to use the tool: for a single hop mapping. It mentions polling with id_map_poll and implies multi-hop scenarios require chaining, though this is detailed more in the input schema. Explicit exclusions for non-safe hops are in the schema but not in the description.

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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TDQS

A3.6/5.0
Disambiguation4/5

Most tools have highly specific purposes (e.g., crispr_grna_design vs base_editing_design vs prime_editing_design). However, there is some overlap in sequence analysis tools (characterize_sequence, sequence_report) and plasmid annotation tools (plasmid_annotate vs plasmid_deep_annotate) which could cause confusion.

Naming Consistency3/5

The naming pattern is largely consistent with snake_case verb_noun or noun_descriptor (e.g., primer_design, plasmid_annotate, fastq_trim). However, there are exceptions like 'batch', 'workflow', 'gc_content', and 'cloning_diagnose' which don't follow the verb_noun pattern consistently. Also, some names are phrases like 'golden_gate_from_parts'.

Tool Count2/5

With 101 tools, this server is extremely large and likely overwhelming for agents. Even for a comprehensive bioinformatics toolkit, this exceeds a manageable scope, risking agent confusion and inefficient tool selection. A more modular approach would be advisable.

Completeness4/5

The tool surface covers a wide range of bioinformatics workflows including sequence analysis, primer design, cloning, CRISPR, NGS, expression analysis, and data export. There are minor gaps such as lack of a dedicated protein structure prediction tool and limited off-target genome coverage, but overall the set is impressively complete for its domain.

Resources