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GonzaloTorreras

ai-dememory

Review Plan

memory.review_plan
Read-only

Retrieve structured review plans for memory items, specifying LLM, human, and validation steps per review kind.

Instructions

Return mode-specific LLM, human, and validation steps for a review kind.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoinbox

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYes
modeYes
policyYes
summaryYes
required_checksYes
forbidden_actionsYes
allowed_llm_actionsYes
required_human_actionsYes
Behavior3/5

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

Annotations indicate readOnlyHint=true and destructiveHint=false, so the description aligns as a read-only operation. The description adds that it returns steps for a given kind, but does not elaborate on other behavioral aspects like permissions or output limitations.

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, focused sentence with no unnecessary words. It efficiently conveys the core function.

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?

While the description is brief, it covers the basic purpose. However, it lacks explanation of what the returned plan contains or why different kinds exist. The presence of an output schema reduces the need for return value details, but the description could still be more informative about the plan structure.

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?

Schema description coverage is 0%. The description mentions 'review kind' which loosely maps to the 'kind' parameter, but does not explain the meaning or use of each enum value. The agent must infer from the enum list in the schema.

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 'return' and the resource 'mode-specific LLM, human, and validation steps for a review kind.' It differentiates from sibling tools by specifying it returns a plan of steps, not actual reviews or conflicts.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives. The description does not provide context for selecting this tool over other review-related 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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