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codeyoc

RepairDesk MCP Server

by codeyoc

repairdesk_tickets

Search and retrieve repair tickets by status, date, keyword, or technician. Get full details for any ticket ID.

Instructions

Search and look up repair tickets. List tickets filtered by status, date, keyword, or tech. Get full details by ticket ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
actionYes"list" to search, "get" for specific ticket
statusNoFilter by status (Pending, In Progress, Repaired, etc.)
keywordNoSearch keyword (customer name, device, etc.)
to_dateNoEnd date as Unix timestamp
pagesizeNo
from_dateNoStart date as Unix timestamp
ticket_idNoTicket ID (for action=get)
assigned_toNoFilter by assigned employee ID
Behavior3/5

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

With no annotations provided, the description carries the full burden of disclosing behavior. It uses read-oriented verbs ('search', 'look up', 'list', 'get') implying a non-destructive operation, but it never explicitly states that no changes are made. It also discloses filtering capabilities but omits details like pagination behavior or any side effects, which is a moderate gap for a read tool.

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 two sentences with no fluff. It front-loads the primary action and then lists the filter options in a logical order. Every word contributes to understanding the tool's purpose and usage.

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

Completeness4/5

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

For a search tool with no output schema and moderate complexity (9 parameters, but only one required), the description covers the main actions (list with filters, get by ID). It does not explicitly mention pagination or the response format, but given the simple read nature and the schema covering parameters, it is reasonably complete. A slightly more detailed mention of return contents would push it higher.

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?

Schema coverage is 78% (slightly below the high threshold), so the description partially compensates by enumerating filter categories (status, date, keyword, tech) and mentioning 'get by ticket ID'. This maps to several parameters, but it adds little beyond the schema's own descriptions, which already explain each parameter's purpose. Overall, it meets the baseline for a moderately covered schema.

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 identifies the tool as a search/lookup for repair tickets with specific verbs (search, look up, list, get) and a resource (repair tickets). It effectively conveys the read-only nature, though it does not explicitly mention the sibling write tool or contrast itself, so it stops short of full differentiation.

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 implies the tool is for reading/searching but provides no explicit guidance on when to use this tool versus alternatives like repairdesk_tickets_write. There are no statements about when not to use it or prerequisites, leaving the agent to infer usage context from the action enum and filter descriptions.

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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