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GonzaloTorreras

ai-dememory

Archived Review Recommendation Status

memory.review_recommendation_archive_status
Read-only

List archived accepted or rejected advisory recommendation artifacts with optional filters for kind and outcome status.

Instructions

List archived accepted/rejected advisory recommendation artifacts without moving files.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo
limitNo
offsetNo
recursiveNo
archive_rootNoarchive/review-recommendations
invalid_offsetNo
outcome_statusNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
offsetYes
enabledYes
filtersYes
invalidYes
has_moreYes
kind_countsYes
next_offsetYes
total_countYes
archive_rootYes
next_actionsYes
writes_filesYes
invalid_countYes
status_countsYes
accepted_countYes
invalid_offsetYes
mutates_systemYes
rejected_countYes
returned_countYes
recommendationsYes
invalid_has_moreYes
invalid_next_offsetYes
invalid_returned_countYes
writes_canonical_memoryYes
applies_review_decisionsYes
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description adds value by specifying 'without moving files'. However, it does not elaborate on pagination, filtering behavior, or response structure beyond what output schema might cover.

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 a single sentence, front-loads the verb and object, and contains no extraneous words. It is appropriately sized for its purpose.

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?

For a tool with 7 parameters and zero schema descriptions, the description is too brief to fully contextualize usage. It covers only filtering by outcome_status, while ignoring other parameters and behavioral details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must compensate but only hints at outcome_status via 'accepted/rejected'. It does not explain the purpose of kind, limit, offset, recursive, archive_root, or invalid_offset, leaving the agent to infer from names and enum values.

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 clearly states the verb 'List' and the specific resources 'archived accepted/rejected advisory recommendation artifacts'. It distinguishes from sibling tools like review_recommendations by focusing on archived statuses and adding the safety note 'without moving files'.

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 implies the tool should be used to view archived recommendation artifacts without altering them, but does not explicitly contrast with alternatives like review_recommendations or provide when-not-to-use guidance.

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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