Jean — Molecular Biology & Genomics

read_mgf

Read-only

Read the MS/MS spectra of a Mascot Generic Format (MGF) file: each spectrum's title, precursor m/z, precursor intensity, declared charge states and peak list, interpreted as pyteomics reads MGF (validated on every spectrum of PXD000001).

Input Schema

Name	Required	Description
`text`	Yes	the MGF file's contents.
`title`	No	return only the spectrum with this title; empty returns every spectrum.
`_files`	No	The project: record references shaped like _subject. Their records become library documents a tool names in sequences/parts/document; a trace or alignment is found by file name.
`_subject`	No	The record to act on: exactly one of sequence, accession (+source), sample (an id from list_samples) or file ({name, text} or {name, base64}); record_index picks one record of several.

Output Schema

Name	Required	Description	Default
`count`	Yes	spectra returned
`spectra`	Yes	one row per spectrum: title, precursorMz, precursorIntensity, charges, mz, intensity

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 20, 2026

TDQS

A3.9/5.0

Behavior4/5

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

The description adds significant behavioral context by detailing the specific fields it extracts (m/z, intensity, etc.). Furthermore, the note about validation on PXD000001 adds valuable data reliability context beyond the basic read-only hint.

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 definition is presented as a dense but efficient single statement. Every part of the sentence contributes directly to defining the tool's input, output, and data interpretation scope.

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

Completeness2/5

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

Given the high complexity and the presence of nested context objects like `_subject` and `_files`, the description is incomplete. It details the file content but fails to explain how the context parameters influence the reading behavior or what the output structure looks like.

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?

Since schema coverage is 100%, the baseline is high. The description effectively compensates by clarifying the semantic meaning of the `title` parameter, framing it as a precise filtering mechanism for the returned spectra.

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 purpose is exceptionally clear, using the specific verb 'Read' and naming the exact resource, 'Mascot Generic Format (MGF) file.' It also specifies the valuable metadata extracted, such as precursor m/z and charge states.

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?

It provides specific usage guidance for the `title` parameter by explaining it functions as a spectrum filter. However, it offers no comparative guidance on when to use this tool versus others for similar data types (e.g., mzml files).

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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