workbench

Hydrophobicity Profile

protein_hydrophobicity

Read-onlyIdempotent

Sliding-window hydropathy/hydrophobicity profile (ProtScale-style) over a published amino-acid scale.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`scale`	No	Amino-acid scale. Kyte-Doolittle and Eisenberg are hydrophobicity; Hopp-Woods is hydrophilicity.	Kyte-Doolittle
`window`	No	Sliding-window size (clamped to an odd number ≥ 1).
`sequence`	Yes	Protein sequence (one-letter amino-acid codes; non-AA characters ignored).

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already declare read-only and idempotent hints. The description adds meaningful behavioral details: sliding-window approach, use of published scales, and handling of non-AA characters. 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?

Single, efficient sentence that immediately conveys the core functionality. No extraneous words, front-loaded with key information.

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 schema and annotations cover the needed details, the description is largely complete. However, the output format ('profile') is vague; mentioning that it returns a list of scores per window position would improve completeness. Still adequate for a low-complexity tool.

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%, so the schema fully documents parameters. The description adds context like 'ProtScale-style' but does not provide additional meaning beyond what is in schema descriptions. Baseline score 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 specifies the tool computes a sliding-window hydropathy/hydrophobicity profile, referencing ProtScale and published amino-acid scales. It distinctively names the resource (protein sequence) and the operation (profile computation), differentiating it from broader sibling tools like 'protein_properties'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives such as 'protein_properties' or 'codon_adaptation_index'. The context is implied by the tool name, but the description does not provide conditions or exclusions to aid selection.

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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