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Glama

record_objection

Log a subject's GDPR Art. 21 objection; thereafter all reads and searches suppress their records until the objection is resolved.

Instructions

GDPR Art. 21: record the subject's objection and stop serving their records. From this call on, every read that searches or lists the store withholds every record whose source resolves to subject, including later writes, until the objection is resolved: recall and its variants, memory_index, verify_claim and check_conflict, and why_recalled explains such a record without quoting it. Every server on this store honours it from its next call. get(id) still returns a record by its exact id, and the records stay exportable under Art. 15 (export_subject); erasure is forget_subject. ground is own_situation (21(1)) or direct_marketing (21(2), never overridable); scope is all or profiling.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actorYes
scopeNoall
groundYes
subjectYes
request_idNo
allow_ambiguousNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv3.5.1

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so thoroughly: it discloses propagation to every server, coverage of later writes, which read tools are affected, the special behavior of why_recalled, and the meanings of ground and scope. This goes far beyond a simple mutation warning.

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

Conciseness5/5

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

The description is dense but every clause adds necessary operational information. The core purpose is front-loaded, and the remaining detail is organized into clearly scoped behavioral rules and parameter notes without redundancy.

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 GDPR state-changing tool with no annotations and no output schema, the description covers side effects, scope, exceptions, and sibling boundaries remarkably well. It is missing only a few parameter-level details (actor, request_id, allow_ambiguous) and any mention of response or error behavior, which keeps it from a perfect score.

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?

The description explains ground (own_situation vs direct_marketing) and scope (all or profiling), and indirectly clarifies subject as the source identity. However, with 0% schema coverage, actor, request_id, and allow_ambiguous remain unexplained, so the description does not fully compensate for the schema's silence.

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: 'record the subject's objection and stop serving their records.' It also distinguishes itself from sibling operations by explicitly carving out get(id), export_subject, and forget_subject, so an agent can tell exactly what this tool does and does not do.

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?

It states the triggering condition (GDPR Art. 21 objection), the effective window ('until the objection is resolved'), and names alternatives: export under Art. 15 uses export_subject, erasure uses forget_subject. It also clarifies that exact-id reads via get(id) remain allowed, which prevents misuse.

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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