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data.delete

Permanently erase user data (page, profile, or all) for GDPR Art. 17/CCPA compliance. Cascade deletes related records and removes embedding-backfill queue jobs to prevent data resurrection. confirm: true required.

Instructions

GDPR Art.17「忘れられる権利」/ CCPA §1798.105 に基づくデータ完全削除。page(全関連テーブルCASCADE DELETE)、profile(嗜好プロファイル完全削除)、all_user_data(全ユーザーデータ一括削除)から選択。confirm: true 必須。target=page / all_user_data では DB 削除前に embedding-backfill Queue の滞留ジョブ(7カテゴリ)も削除し、非同期 backfill による削除済みデータ復活を防止する。GDPR Art.17 / CCPA §1798.105 Right to Erasure. Permanently deletes all data for the specified target. Supports page (CASCADE DELETE), profile (hard delete), all_user_data (bulk delete). confirm: true is required. For target=page / all_user_data, embedding-backfill queue jobs (7 categories) are also removed before DB deletion to prevent async backfill from resurrecting erased data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYes削除対象 / Deletion target: page (web page + all related data), profile (preference profile + signals), all_user_data (all pages + profile)
idYes対象ID(UUIDv7形式) / Target ID (UUIDv7 format). page → web_page.id, profile/all_user_data → preference_profile.id
reasonYes削除理由(GDPR監査要件、1-500文字) / Deletion reason (GDPR audit requirement, 1-500 chars)
confirmYes削除確認フラグ(true必須、誤削除防止) / Deletion confirmation flag (must be true)
page_idsNoページID配列(target=all_user_data時のみ、最大100件) / Page IDs (only for target=all_user_data, max 100)
Behavior5/5

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

Annotations show readOnlyHint=false and idempotentHint=false, matching destructive nature. Description adds critical details: cascade delete, queue job removal to prevent resurrection. No contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is bilingual (Japanese first, then English), which adds redundancy. While comprehensive, it could be more concise by merging both languages into one. Core info is front-loaded but length may reduce readability.

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?

No output schema exists, but the description does not mention what the tool returns (e.g., success message, deleted count). An agent cannot know the response format. This is a significant gap for a destructive 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?

Schema coverage is 100% with good descriptions. The description adds value by explaining the embedding-backfill queue removal for target=page/all_user_data and clarifying that confirm:true is mandatory, supplementing the 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?

Description clearly states the tool performs permanent data deletion under GDPR/CCPA for specific targets (page, profile, all_user_data). Verb 'delete' plus resource 'data' with explicit legal context. Siblings include only data.export (export, not delete), so no confusion.

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?

Description explains when to use (GDPR/CCPA deletion) and provides target-specific guidance. No explicit when-not-to or alternatives (e.g., preference.reset might be softer), but context is clear enough for an agent to differentiate from siblings.

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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