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ms-data-parser

console_cleanup

DestructiveIdempotent

Lists or deletes only artifacts recorded in analysis-job.json for a specific job, preventing mixed MS-DIAL output batches and protecting raw data; defaults to a dry-run listing.

Instructions

あるジョブが生成したファイルだけを一覧・削除します(既定は一覧のみ)。

MS-DIAL Console は生データフォルダ側にも生成物を出すため、再実行のたびに 別タイムスタンプのアライメント一式が同じフォルダへ積まれます。放置すると 「複数バッチ混在フォルダ」になり、どれが今回の結果か分からなくなります。

消す対象は analysis-job.json が記録した生成物だけです。タイムスタンプの 推測では消しません(別バッチの成果物を巻き込むため)。記録が無いジョブは NO_JOB_OUTPUT で拒否します。生データ(.wiff 等)には触れません。

dry_run: True(既定)なら一覧を返すだけ。False で実際に削除します。 削除後、ジョブの status は cleaned になります(生成物を指したまま completed で残ると、dataset_load が存在しないファイルを読もうとします)。

Input Schema

NameRequiredDescriptionDefault
dry_runNo
job_pathNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the annotations (destructiveHint=true, idempotentHint=true, readOnlyHint=false), it discloses the crucial safety design: deletion is driven only by the analysis-job.json manifest, never by timestamp guessing, raw data such as .wiff is untouched, and jobs without a record are refused. It also explains the post-delete side effect that the job status becomes `cleaned` and why that matters to dataset_load.

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 default behavior and the deletion scope are front-loaded, and the bold emphasis on exactly what gets deleted is well placed. The background paragraph on MS-DIAL Console is slightly verbose but justifies why the tool exists.

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?

For a default-no-op destructive mutation tool with no output schema, it covers scope, refusal behavior, and status transition adequately. The remaining gap is the unresolved job_path semantics and what the returned listing actually contains.

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?

Schema description coverage is 0%, so the description must carry the parameter burden. It fully explains dry_run (default True = list only, False = actually delete) but says nothing about job_path, which is the key selector parameter and defaults to null, leaving the agent to infer its format and meaning.

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 opening line gives a specific verb pair (list/delete) with an explicit scope: only files generated by one job, defaulting to listing. The follow-up explains the exact domain problem (MS-DIAL Console piling up timestamped alignment sets in the raw-data folder), so an agent can tell this is the targeted cleanup tool rather than a generic file remover.

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?

It clearly states the triggering situation (repeated runs leave mixed batches and you can no longer tell which result is current) and the guardrail that only artifacts recorded in analysis-job.json are touched, with NO_JOB_OUTPUT returned for unrecorded jobs. It does not, however, point to specific sibling alternatives (e.g. job_list / console_status) for inspecting before cleaning.

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