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vbcherepanov

total-agent-memory

memory_get

Read-onlyIdempotent

Retrieve full content for selected knowledge record IDs, complementing memory_recall's index mode. Use after picking specific IDs from an index to get complete details.

Instructions

Batched fetch by ID — complement to memory_recall(mode='index'). Returns full content for ONLY the IDs the caller chose after inspecting an index. Typical 3-layer flow: recall(mode='index') → pick IDs → memory_get(ids=[...]).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsYesKnowledge record IDs (max 50 per call; extras are silently dropped)
detailNo'summary' truncates content to 150 chars, 'full' returns everythingfull

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds that it returns full content only for selected IDs, which clarifies output behavior but does not introduce additional side-effect or permission information. This is slightly above baseline because the description reinforces the non-destructive nature.

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 concise, using three sentences to convey purpose, relationship to sibling tool, and usage flow. No redundant or filler content; every sentence adds value.

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

Completeness5/5

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

Given the simple parameter set and absence of an output schema, the description fully equips an agent to decide when and how to use the tool. It provides the necessary context about the intended workflow and the tool's role within it, making it complete for this context.

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

Parameters3/5

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

The schema already provides 100% coverage for both parameters including the enum and default for 'detail', and the description of 'ids' mentions the maximum and silent dropping in the schema. The description itself does not add further parameter semantics beyond what the schema already states, so it stays at the baseline of 3.

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 'fetch' and the resource 'memory by ID', and explicitly distinguishes it from the sibling tool memory_recall by describing it as a complement and specifying its role in a typical flow (after index inspection). This makes the purpose unambiguous.

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

Usage Guidelines5/5

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

The description explicitly names the alternative tool (memory_recall(mode='index')) and provides a clear usage flow: recall index first, then pick IDs, then call memory_get. This leaves no doubt about when to use this tool versus others.

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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