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Glama

get_chat_history

Retrieve paginated coaching or chat logs for a client, filtered by conversation ID or date range, to review message history.

Instructions

Paginated coaching/chat conversation logs.

Args: conversation_id: Restrict to one conversation thread. limit: Max messages to return (default 50).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
end_dateNo
client_idYes
start_dateNo
conversation_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden and does not discharge it. 'Paginated' is a useful trait, but there is no indication that access is scoped to a specific client_id, whether the logs are sensitive/audited, what permissions are required, or how paging beyond the first page is achieved.

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

Conciseness3/5

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

The prose line is front-loaded and tight, but the pseudo-args block only restates two schema fields and leaves the rest out, so the structure spends words without covering the surface it implies it covers.

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?

With an output schema present the return shape need not be described, but for a 5-parameter tool with no annotations, three undocumented parameters (including the required one) and no usage routing make the definition insufficient for correct invocation.

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, and it only documents 2 of 5 parameters (conversation_id, limit). The required client_id and the start_date/end_date date-range filters — the parameters most likely to be misused — are completely unexplained.

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 names the exact resource — coaching/chat conversation logs — and adds the pagination characteristic, which clearly distinguishes it from the health-metric siblings (sleep, exercise, nutrition, trends). It lacks an explicit verb, but 'get_chat_history' plus 'conversation logs' leaves no ambiguity about what is returned.

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 statement of when to use this tool versus alternatives, no prerequisites, and no exclusions. An agent gets no help deciding between this and the many other data-retrieval siblings.

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