workbench

Submit a protein for domain/GO annotation

protein_annotate_submit

Read-onlyIdempotent

Submit a protein sequence to EBI InterProScan for domain architecture, family and GO-term annotation. Returns a jobId immediately — the job itself takes minutes; poll it with protein_annotate_poll.

Input Schema

TableJSON Schema

Name	Required	Description
`appl`	No	Restrict to one member database (e.g. "PfamA"); omit to run EBI's defaults across all of them.
`goterms`	No	Include GO-term cross-references.
`sequence`	Yes	Protein sequence, one-letter code (FASTA header, if any, is stripped).

TDQS

A4.2/5.0

Behavior4/5

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

The description discloses that the job is asynchronous and takes minutes, which goes beyond annotations (readOnlyHint, idempotentHint). No contradiction with annotations. The description adds behavioral context about immediate return of jobId and need for polling.

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, both front-loaded with essential information. Every word adds value, with no redundancy or filler. Efficient and clear.

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 three parameters are well-described in the schema, the description sufficiently covers the workflow. It mentions the asynchronous nature and need to poll, but could optionally specify the format of jobId. Overall adequate for a submission tool with no output schema.

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 coverage is 100% with clear descriptions for each parameter. The description does not add additional parameter-level meaning beyond the schema. It restates the overall function but not per-parameter details. 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 verb (submit), resource (protein sequence to EBI InterProScan), and output (jobId). It distinguishes itself from the sibling tool 'protein_annotate_poll' by indicating that this is the submission step and polling is done separately.

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 explicitly states the workflow: submit and then poll with protein_annotate_poll. It does not list exclusions or alternatives, but the context makes it clear that this is the submission step. The requirement for a protein sequence is implied but not stated as a prerequisite.

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.

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