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session_get

Read a session's turns and context entries, optionally filtered by section, to retrieve specific conversation data from mnemoth's persistent memory.

Instructions

Read a session: turns and context entries, optionally filtered by section.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
datasetNo
sectionsNo
session_idYes
include_turnsNo

Schema Changelog

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

  1. First observedv0.2.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations provided, the description must carry the behavioral disclosure burden. It does convey that the operation is a read and that results are optionally filtered by section. However, it does not mention default behavior like include_turns=true, dataset scoping, or any quirks of the returned data.

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, front-loaded sentence with no filler. It states the operation, the content, and the main optional modifier efficiently.

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

Completeness2/5

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

For a tool with four parameters, no output schema, and no annotations, this description is under-specified. It omits dataset semantics, the role of include_turns, section value expectations, and any differentiation from similar siblings. An agent would need to inspect or guess to call it with confidence.

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%, so the description must compensate for all four parameters. It only adds meaning for 'sections' ('filtered by section') and vaguely implies 'include_turns' through 'turns and context entries'. The 'dataset' parameter is entirely unexplained, and the include_turns default is not surfaced.

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

Purpose4/5

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

The description uses a specific verb ('Read'), names a concrete resource ('a session'), and identifies the payload ('turns and context entries'). It is clear, though it does not explicitly differentiate itself from sibling read tools like session_timeline, recall, or history.

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

Usage Guidelines3/5

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

The phrase 'Read a session' implies its purpose and provides basic context for when to call it. However, it gives no guidance about when to prefer this tool over the many read-adjacent siblings, nor does it mention any exclusions or prerequisites.

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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