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Multi-omics methods section draft / 多组学论文段落

omics_methods_draft
Read-only

Multi-omics methods section draft / 多组学论文段落 | USE WHEN: the user wants a methods section for a multi-omics paper, assembled only from the analyses they actually ran | ALIASES: 多组学方法, 方法学段落, RNA-seq 方法, methods section, omics methods | RETURNS: 论文段落

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "omics_methods_draft"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is known. The description adds one meaningful behavioral constraint (assembled only from analyses actually run, implying no fabrication), but it never explains where the analyses are drawn from given zero parameters, nor what 'RETURNS: 论文段落' yields concretely.

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 pipe-delimited layout front-loads the use case and keeps the whole definition to a few short segments with no filler prose. The repeated bilingual title and the minimal 'RETURNS: 论文段落' segment contribute little beyond decoration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no parameters, no output schema and a closed-world annotation, the description must carry the whole burden of explaining inputs and outputs. It states the source constraint but not how the analyses are located or what the returned paragraph looks like, leaving a real gap for an agent trying to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so there is no parameter semantics for the description to carry and the baseline of 4 applies. The one related gap is that the description does not say how the tool obtains its input context, which matters more here than for a parameterized tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource: drafting a methods section for a multi-omics paper, and it constrains the content to analyses the user actually ran. It does not explicitly distinguish itself from siblings like proteomics_methods_draft or section_writer, leaving the agent to infer the multi-omics scope from the name alone.

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 'USE WHEN' clause gives clear triggering context: the user wants a methods section for a multi-omics paper. It stops short of stating when NOT to use it or naming the obvious alternative (proteomics_methods_draft, section_writer) for single-omics or non-methods writing.

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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