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GonzaloTorreras

ai-dememory

List Review Recommendations

memory.review_recommendations
Read-only

Retrieve review recommendations for conflict, false-positive, inbox, maintenance, or promotion items, filtered by status and policy violations, without applying outcomes.

Instructions

List advisory review recommendation artifacts without applying review outcomes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo
outcome_statusNo
policy_violations_onlyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
enabledYes
filtersYes
invalidYes
total_countYes
next_actionsYes
writes_filesYes
allowed_countYes
invalid_countYes
pending_countYes
accepted_countYes
mutates_systemYes
rejected_countYes
recommendationsYes
latest_created_atNo
recommendation_dirYes
policy_violation_countYes
writes_canonical_memoryYes
applies_review_decisionsYes
requires_human_approval_countYes
Behavior3/5

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

Annotations already provide readOnlyHint=true and destructiveHint=false, establishing the tool is safe. The description adds the behavioral detail that outcomes are not applied, which aligns with annotations. It does not contradict and provides modest extra context.

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 short sentence (9 words) that front-loads the action 'List' and is highly concise with no wasted words.

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

Completeness3/5

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

The tool has an output schema (not shown but indicated), so return values are handled. However, the description does not explain what the output contains or how to use the parameters. While the tool is simple, the lack of parameter guidance makes it less complete.

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 should explain parameters but does not mention them at all. The parameters (kind, outcome_status, policy_violations_only) are not described, leaving agents to infer meaning solely from enum values and type, which is insufficient.

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 uses a specific verb 'List' and clear resource 'review recommendation artifacts', and explicitly states the tool does not apply review outcomes, distinguishing it from siblings like memory.review_recommendation_outcome.

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 clearly implies the tool is for viewing recommendations without committing changes, providing context for its use. However, it lacks explicit when-not-to-use guidance or mention of alternatives among the numerous sibling tools.

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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