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gl_archive_purge

Purge archived accounting periods after ten-year retention expires, recording the reason and keeping a purge record; refuse with a dated record for any period still inside the retention window.

Instructions

Purge archived periods whose OR 958f ten-year retention has expired, with a recorded reason. Deletes ARCHIVE data only (structurally incapable of touching a live journal row), keeps a purge record where the periods were, and refuses inside the retention window with the date, recording the refusal: that record is the answer a data subject receives. Requires confirmed:true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonYes
periodToYes
confirmedNo
periodFromYes
workspaceIdYes
idempotencyKeyYes

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?

With no annotations, the description carries the full burden and does exceptionally well: it explicitly states that only ARCHIVE data is deleted, that live journal rows are structurally untouchable, that a purge record is kept, and that refusals inside the retention window are recorded with the date. This is exactly the behavioral disclosure a destructive tool needs.

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 dense and front-loaded with the core purpose, then safety and refusal behavior. It is longer than a single sentence but every sentence earns its place; the only slight blemish is the unexplained 'OR 958f' abbreviation.

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 destructive purge tool with no annotations and no output schema, this description covers the essential operational context: what gets deleted, what is kept, refusal behavior, and confirmation. It does not explain idempotency key semantics or return value, but those are minor against the strong behavioral coverage.

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 compensate. It adds meaning for 'confirmed' (requires true), 'reason' (recorded), and the period range (purge archived periods), but it leaves 'idempotencyKey' and date format unaddressed. Partial compensation but not enough for six parameters.

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 names a specific verb ('purge') and resource ('archived periods') with a precise condition (ten-year retention expired). This clearly differentiates the tool from gl_archive_query, gl_archive_preview, or gl_archive_import, since it is the only one that deletes archived periods.

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?

The description states when to use the tool (when retention has expired), what is required (confirmed:true), and describes the refusal behavior inside the retention window. It does not explicitly name alternatives or say 'use X instead', but the context is clear enough for an agent to decide.

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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