Skip to main content
Glama
ac0033

agent-memory

by ac0033

memory_review_resolve

Resolve pending memory reviews by approving, modifying with new content, or discarding items to finalize memory storage.

Instructions

裁决一条复核待办:approve 确认入库 / modify 以 new_content 替换正文后入库 / discard 丢弃。queue_file 取 memory_review_list 返回里的 file 字段

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYes
queue_fileYes
new_contentNo
Behavior4/5

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

With no annotations provided, the description carries the full disclosure burden. It accurately conveys the side effects of each action: approve persists, modify replaces content before persisting, and discard drops the item. It also explains the provenance of queue_file. However, it does not disclose whether the queue item is consumed after resolution or whether new_content is mandatory for the modify action, leaving minor gaps.

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 compact sentence that lists the actions and their meanings, followed by a short clarification of where queue_file originates. Every clause adds necessary information 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?

The description covers the core workflow, parameter sourcing, and action semantics, which is sufficient for an agent to invoke the tool correctly. It omits return values, explicit requirement of new_content for modify, and post-resolution queue state, but these are secondary for a narrowly scoped resolution tool. Given the lack of an output schema, this is reasonably complete.

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

Parameters5/5

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 fully documents all three parameters: action enumerates the valid values (approve/modify/discard), queue_file is tied to the output of memory_review_list, and new_content is defined as the replacement body for modify. This resolves the ambiguity left by the bare 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 states a specific verb (裁决/adjudicate) and resource (复核待办/review todo), then enumerates the permissible actions (approve, modify, discard), making the tool's purpose unmistakable. It also distinguishes itself from the sibling memory_review_list by focusing on the resolution step rather than the listing step.

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 explicitly tells the agent that queue_file comes from the return of memory_review_list, effectively positioning this as the follow-up to that tool. It names the source of a key parameter and implies a list-then-resolve workflow, though it does not formalize when-not-to-use or list alternative tools for this specific action.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ac0033/agent-memory'

If you have feedback or need assistance with the MCP directory API, please join our Discord server