report_issueデータの誤りに気づいたら、利用者の同意を得たうえで報告します。 報告してよいか、必ず利用者に確認してから呼び出してください。
報告した数値が自動で直ることはありません。運営が原本（有価証券報告書・ 決算短信など）を確認したうえで手動で修正します。
1日あたり10件までです。上限に達すると daily_limit エラーになります。
銘柄コードは英字入り（140A 等）も指定できます。
※ 本データは情報提供を目的とし、投資助言・推奨ではありません。
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | 対象の証券コード（例: 7203、140A） | |
| field | No | 誤りがある指標・項目名（任意、例: ROE、配当性向） | |
| message | Yes | 誤りの内容（1〜500文字）。何がどう違うと思うかを具体的に書いてください | |
| sourceUrl | No | 根拠となる情報源のURL（任意、http/https のみ） | |
| fiscalYear | No | 対象の年度（任意、例: 2025年3月期） |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes well beyond the annotations (readOnlyHint=false, idempotentHint=false): it discloses that submissions do NOT auto-correct data, that operators manually verify against 有価証券報告書/決算短信, that consent must be obtained, and that a 10-per-day rate limit returns a daily_limit error. These are non-obvious operational facts that annotations cannot convey.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The consent requirement and the no-auto-correction fact are front-loaded where they matter, and the rate limit is stated compactly. The closing investment-advice disclaimer is boilerplate rather than operational, but it is short and plausibly required.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 tells the agent everything needed to call correctly and set user expectations: who reviews the report, the consent gate, the daily cap, and the accepted code format. All 5 parameters are covered by the schema, so nothing is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents code, field, message, sourceUrl, and fiscalYear. The description's note that codes may contain letters (140A) duplicates the example already present in the schema, adding no new meaning. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb+resource ('データの誤りに気づいたら…報告します') with no ambiguity about what is reported or to whom. No sibling tool performs user-submitted error reporting, so there is nothing to confuse it with among the get_*/screen_*/watchlist tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states the trigger ('データの誤りに気づいたら') and a hard prerequisite ('必ず利用者に確認してから呼び出してください'). It also names the failure condition the agent will encounter (daily_limit after 10 reports/day), which is exactly the when-not guidance an agent needs.
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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