workbench

Gene/Target Dossier

gene_dossier

Read-onlyIdempotent

A gene/drug-target dossier fanned out to five independent sources in one call: Open Targets (function, tractability, top associated diseases), an NCBI/UniProt plain-English function summary, ChEMBL (known drugs and their mechanism/clinical phase, cross-referenced with indications), ClinicalTrials.gov (trials by gene/condition term), and Europe PMC (top cited papers). Each source fails independently — a down source returns null/empty for its own section rather than failing the whole call, and every failure is listed in "sourceErrors" rather than silently omitted.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`gene`	Yes	A human gene symbol ("TP53") or Ensembl gene ID ("ENSG00000141510").

TDQS

A4.1/5.0

Behavior5/5

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

Annotations already indicate read-only and idempotent behavior. The description adds critical detail: each source fails independently (null/empty for its section) and failures are listed in 'sourceErrors' rather than aborting the call. This goes well beyond annotation information.

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 a single sentence structure broken into two sentences, packing a lot of detail. While it is somewhat long, every part is informative and front-loaded with the core function. Minor redundancy ('fanned out' and 'in one call') could be trimmed.

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 no output schema, the description adequately covers the expected result shape: per-source sections with potential null/empty, and a sourceErrors list. It names each source's contributions. However, it does not specify whether the output is flat or nested, which could be clarified further.

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?

There is only one parameter (gene) with 100% schema coverage in the description. The tool description adds no further parameter-level detail beyond what the schema provides, so a 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 that this tool generates a multi-source dossier for a gene/drug-target by aggregating from five distinct sources. It lists each source and what it provides (Open Targets, NCBI/UniProt, ChEMBL, ClinicalTrials.gov, Europe PMC). This distinguishes it from siblings like gene_expression or gene_model which focus on single aspects.

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 implies 'in one call' for a comprehensive overview, but does not explicitly specify when to use this tool versus alternatives like web_search or individual source tools. There is no guidance on prerequisites or limitations, though the parameter description restricts to human genes.

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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