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forget_subject

Erase all data about a subject per GDPR Article 17, including linked references, and return a deletion receipt. Preview with dry run; use exact mode to avoid deleting colliding subjects.

Instructions

Right-to-erasure by SUBJECT (GDPR Art.17 / DSR): delete every memory about subject AND scrub its id from survivors' links/supersession pointers, so it can't resurface via recall or consolidation. basis records the legal/operational reason. Returns a receipt (erased count, ids, scrubbed_links, tombstones, request_id, coverage, residue_in_store) you can keep as evidence.

RUN IT WITH dry_run=True FIRST. This cascades through inherited lineage, so it commonly erases more than the records that name the subject: the preview returns {would_erase, direct, inherited, sample, also_carrying} and changes nothing. inherited is the count you cannot predict, and also_carrying names the OTHER subjects whose data goes down with this request — one erasure is quietly several more often than not.

If the call raises AmbiguousSubject, the subject you passed canonicalizes to the same key as a DIFFERENT source in the store (e.g. two people under one host: crm.example.com/alice and crm.example.com/bob), so erasing would delete a third party's records. Read the message, confirm which subject is meant, and then choose: exact=True erases only the records whose RAW source string is this subject (plus their lineage) and LEAVES the colliding subject alone — prefer it, it completes the DSAR without touching anyone else. allow_ambiguous=True erases every colliding subject together, so pass it only if you really mean that. This surface used to offer allow_ambiguous alone and this text named it as THE answer, which pointed the caller at the over-deleting half of the choice; measured, that erased a third party's record where exact=True kept it. Collisions are not rare: canonicalisation is host/collection level, so 'employee/1001' and 'employee/1002' share a canonical form.

authorized_by (the authorising principal's public key) and authorization (their signature over erasure_challenge(subject, request_id)) are recorded in the tombstone's auth field — the Art.30 record of WHO authorised the deletion. Neither was on this surface, so every MCP erasure was unattributed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
basisNo
exactNo
dry_runNo
subjectYes
request_idNo
authorizationNo
authorized_byNo
allow_ambiguousNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.20.1

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden, and it does so thoroughly. It discloses cascading lineage erasure, link scrubbing, tombstone auth recording, return receipt contents, AmbiguousSubject conditions, and explicit warnings about third-party data. This goes well beyond generic 'deletes data' and exposes real side effects and edge cases.

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 description is verbose but information-dense and front-loaded with the most critical warning (dry_run). Paragraphs are logically organized: purpose, preview, ambiguity, authorization. The only minor excess is the historical aside about previous surface behavior, which is relevant but could be tightened. Given the high-stakes, complex tool, the length is largely justified.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 8-parameter destructive tool with no annotations and no output schema, the description is remarkably complete. It defines the return receipt fields, explains the preview return structure, details collision resolution, and records auth requirements. An agent has everything needed to invoke correctly and avoid common pitfalls.

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 description coverage is 0%, so the description must explain all parameters, and it does. It defines subject as the target, basis as the legal/operational reason, dry_run as the preview mode, exact vs allow_ambiguous as collision-handling strategies, and authorized_by/authorization/request_id as the auth and audit context. Every parameter receives meaningful explanation beyond its bare schema type.

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 description opens with a precise verb–resource pair: 'Right-to-erasure by SUBJECT (GDPR Art.17 / DSR): delete every memory about `subject` AND scrub its id from survivors' links/supersession pointers'. It clearly distinguishes this from generic erasure tools by emphasizing subject-scoped cascading deletion and GDPR context, leaving no ambiguity about what the tool does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly instructs to run with dry_run=True first, explains when to prefer exact=True over allow_ambiguous=True, and cautions against the over-deleting behavior of allow_ambiguous. It even includes a historical note explaining why exact is the safer default. This is concrete, decision-oriented guidance that directly helps an agent choose correct invocation.

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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