list_conversations
Retrieve message conversations for a school using its school ID.
Instructions
List message conversations for a school.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| school_id | Yes |
Retrieve message conversations for a school using its school ID.
List message conversations for a school.
| Name | Required | Description | Default |
|---|---|---|---|
| school_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It implies a read-only operation ('List') but adds no details about pagination, ordering, return format, or potential side effects. The only added context is the school scope, which is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, six-word sentence that front-loads the verb and resource. It has no redundant information, fluff, or filler, making it exceptionally concise and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple read tool with one parameter and no output schema, so the description doesn't need extensive detail. However, it lacks critical context such as what a 'conversation' includes, whether results are paginated, or how this differs from 'get_conversation'. For a minimal viable description, it is adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the tool has one parameter (school_id). The description's phrase 'for a school' merely restates the parameter name without adding meaningful semantics like format, constraints, or how it affects results. It does not compensate for the schema's lack of documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('List') and resource ('message conversations') with a scope ('for a school'), making the purpose clear. However, it does not explicitly distinguish this from sibling tools like 'get_conversation', relying on the generic list/get distinction rather than explicit differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'get_conversation' or 'list_schools'. The description simply states what it does without giving context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/tdlm/parentsquare-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server