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effytech

Freshservice MCP server

by effytech

create_requester

Create a requester in Freshservice by providing details such as first name, email, phone number, job title, and department. Simplifies user management and ticket tracking.

Instructions

Creates a requester in Freshservice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressNo
background_informationNo
can_see_all_tickets_from_associated_departmentsNo
custom_fieldsNo
department_idsNo
first_nameYes
job_titleNo
languageNo
last_nameNo
location_idNo
mobile_phone_numberNo
primary_emailNo
reporting_manager_idNo
secondary_emailsNo
time_formatNo
time_zoneNo
work_phone_numberNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
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 burden of behavioral disclosure. While 'Creates' implies a write operation, it lacks details on permissions needed, whether the operation is idempotent, what happens on duplicate entries, or error handling. For a mutation tool with 17 parameters and no annotation coverage, this is a significant gap in transparency.

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, efficient sentence with no wasted words. It's appropriately sized for a basic purpose statement, though its brevity contributes to gaps in other dimensions like guidelines and parameter semantics.

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?

Given the complexity (17 parameters, 1 required, mutation operation) and lack of annotations, the description is insufficient. While an output schema exists (which might cover return values), the description doesn't address critical aspects like parameter meanings, usage context, or behavioral traits, making it incomplete for effective tool selection and invocation.

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

Parameters1/5

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

The schema description coverage is 0%, meaning none of the 17 parameters have descriptions in the schema. The tool description provides no information about parameters, not even mentioning key fields like 'first_name' (the only required parameter) or optional ones. This fails to compensate for the lack of schema documentation, leaving parameters entirely 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 clearly states the action ('Creates') and resource ('a requester in Freshservice'), making the purpose unambiguous. However, it doesn't differentiate this tool from sibling tools like 'add_requester_to_group' or 'update_requester', which would require more specific context about when to create versus modify or associate requesters.

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?

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'update_requester', 'filter_requesters', and 'get_all_requesters', there's no indication of prerequisites (e.g., when a requester doesn't exist), exclusions, or comparative use cases, leaving the agent to infer usage from context alone.

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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