Skip to main content
Glama

memoryguard_knowledge_candidates

Review and validate knowledge candidates from your coding agent's memory layer before they are committed, preventing inaccurate data from entering shared context.

Instructions

V2-native knowledge surface.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.7.8

TDQS

D1.8/5.0
Behavior1/5

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

With no annotations provided, the description carries the full burden of disclosing behavior, side effects, or output characteristics. 'V2-native knowledge surface' discloses nothing about what the tool does, whether it reads or writes, or what an agent should expect from calling it.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short but this is under-specification, not effective conciseness. The phrase 'V2-native knowledge surface' does not earn its place because it fails to convey meaning.

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

Completeness1/5

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

Even with no parameters and no output schema, the description must explain enough for an agent to decide whether to invoke the tool. A single vague phrase is severely inadequate, especially given the large set of sibling tools with overlapping 'knowledge' or 'candidate' naming.

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

Parameters4/5

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

The tool has zero parameters, so there is no parameter semantic burden for the description to carry. The baseline of 4 applies because no additional parameter explanation is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'V2-native knowledge surface' contains no verb or resource, and does not state what the tool does. It is an opaque label rather than an explanation, leaving the agent to guess whether the tool lists, generates, or manages candidates.

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?

There is no guidance on when to use this tool or how it relates to siblings such as memoryguard_accept_candidates or memoryguard_knowledge_list. The description provides no context for selection, so the agent receives no usable direction.

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/irisxc4/memoryguard'

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