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systemsomicslab

ms-data-parser

console_method_candidates

Read-onlyIdempotent

Lists usable MS-DIAL method file candidates for a dataset by scanning sibling folders and past runs, so you can select valid parameters before console_plan fails.

Instructions

使えるメソッドファイルの候補を列挙します(console_plan が失敗する前に呼べます)。

MS-DIAL GUI は解析のたびに <project>_param_<終了時刻>.txt をプロジェクト フォルダへ自動保存します。その極性で一度も GUI 実行が無いフォルダには存在 しないため、兄弟フォルダ(POS の隣の NEG 等)と過去 run まで探します。

dataset_root: 生データフォルダ。 polarity: "positive" / "negative"。省略すると極性で区別せず全件返します。 指定すると各候補に usable が付き、一致しないものは needs_polarity_conversion(console_method_template を経由させる)。 omics: 既定 "lipidomics"。None で絞り込みません。 search_dirs: 追加で探すフォルダ。再帰はしません。

候補には比較用の key_params(検出・アライメント条件のうち結果を変える少数)が 付きます。候補が 10 件を超えるときは付きません(戻り値が肥大するため)。

Input Schema

NameRequiredDescriptionDefault
omicsNolipidomics
polarityNo
search_dirsNo
dataset_rootYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare read-only/idempotent/non-destructive, and the description adds genuinely non-obvious behavior: the search silently expands to sibling folders and past runs, search_dirs is non-recursive, and key_params is omitted when more than 10 candidates exist to avoid bloat. These are exactly the surprises an agent needs warned about.

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-loaded with purpose and the console_plan relationship, then a clean per-parameter block. Slightly verbose in the MS-DIAL background paragraph, but every sentence contributes context.

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?

With no output schema, the description still names the return fields (usable, needs_polarity_conversion, key_params) and their conditional presence, which is what an agent needs to interpret results. It stops short of describing the candidate entry shape (path, filename, detection parameters), which is the remaining gap.

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

Parameters5/5

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

Schema coverage is 0%, so the description carries the full burden — and it does: dataset_root, polarity string values plus its effect on the output and on needs_polarity_conversion, omics default of 'lipidomics' with None meaning no filtering, and search_dirs' non-recursive semantics. All four parameters gain meaning beyond the bare schema.

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 and resource ('列挙します' of usable method-file candidates) and immediately scopes it against the sibling workflow ('console_plan が失敗する前に呼べます'). The explanation of where MS-DIAL param files come from makes the tool's role unmistakable versus console_method_template and console_plan.

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?

Gives clear timing context (call before console_plan fails) and routes mismatched-polarity entries to console_method_template via the needs_polarity_conversion flag. No explicit 'do not use when' statement, but the routing guidance is actionable.

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