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systemsomicslab

ms-data-parser

eic_search

Read-only

Search EIC spots by spot ID, m/z, and RT ranges, apply all filters together, and return compact TSV rows with intensity, sample counts, annotations, adducts, and MS/MS counts for lipidomics.

Instructions

EIC スポットを spot ID・m/z 範囲・RT 範囲で検索し、TSV で返す。

指定した条件はすべて AND で掛かる(何も指定しなければ全件)。境界値は含む。 spot_ids は MasterAlignmentID(ARF / ARF2 / .dcl と共通)の完全一致で、 範囲外の ID は注記に列挙する。sort="max_intensity" は各試料のクロマトグラム 最大強度の、そのまた最大値で降順に並べる(強度上位ランキング)。既定は spot_id 昇順。

各行は spot_id rt mz max_intensity num_samples name ontology adduct n_msms。 name / ontology / adduct は同じバッチの .arf2、n_msms は アラインメント .dcl の代表試料 MS/MS のピーク数。- は未取得または precursor 不一致で、0 本ではない。未注釈で n_msms がある行は library_match_feature(spot_id=...) → library_plot_mirror で照合・確認できる。

Input Schema

NameRequiredDescriptionDefault
sortNospot_id
max_mzNo
max_rtNo
min_mzNo
min_rtNo
spot_idsNo
file_pathNo
max_resultsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

readOnlyHint is already declared; the description adds meaningful context beyond it — the TSV row layout, provenance of name/ontology/adduct (from .arf2) and n_msms (from .dcl), that '-' means missing or precursor mismatch rather than zero, and that out-of-range spot IDs are listed in notes. Silent on truncation behavior from max_results, which is a gap for a mutation-free but potentially large result set.

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?

Front-loads purpose and filter semantics before diving into output columns. The column list and provenance notes are dense but justified since no output schema exists; minor density is the only knock.

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?

Without an output schema, the description thoroughly specifies the returned row shape and the meaning of sentinel values, and provides a follow-up workflow for unannotated rows. The unexplained file_path and max_results/truncation semantics keep it short of fully complete for an 8-parameter tool.

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?

With 0% schema coverage, the description carries the burden well: it defines broad scope and semantics for spot_ids, sort (max_intensity vs default spot_id ascending), min/max m/z, and min/max RT with boundary handling. However, file_path and max_results (a default of 20 implying truncation) are never explained, leaving 2 of 8 params undocumented in both schema and description.

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?

States a specific verb (search), resource (EIC spots), filtering dimensions (spot ID, m/z range, RT range) and output format (TSV). An agent can immediately distinguish it from eic_parser and eic_plot_chromatograms.

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?

Explains AND semantics, that no filters means all records, boundary-inclusive behavior, and exact-match semantics for spot_ids. Also routes unannotated but n_msms-bearing rows to library_match_feature → library_plot_mirror as a follow-up. No explicit exclusion of siblings, but context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.