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hvkshetry

Wave MCP Server

by hvkshetry

item

Manage products and services in Wave accounting: create, update, list, search, get, or archive items with fields such as name, price, and tax IDs.

Instructions

Products & services management in Wave.

Operations: Read: list, get, search Write: create, update, archive

Args: operation: One of the operations listed above. item_id: Product ID (base64 string, required for get/update/archive). data: Dict of fields for create/update. Key fields: - name (str, required for create) - description (str) - unitPrice (decimal as string, e.g. "19.99") - isSold (bool) - isBought (bool) - incomeAccountId (str, account ID) - expenseAccountId (str, account ID) - defaultSalesTaxIds (list of tax IDs) query: Search text for search operation (matches name, client-side). page: Page number (default 1). page_size: Results per page (default 50).

Returns: JSON string with product data or {"error": "..."}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
pageNo
queryNo
item_idNo
operationYes
page_sizeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already indicate readOnlyHint=false, destructiveHint=false, and openWorldHint=true. The description adds the return format (JSON string with data or error) and implies mutation via archive, but does not elaborate on behavioral traits like side effects or permissions. It does not contradict annotations.

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

Conciseness4/5

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

The description is well-organized into sections (operations, args, returns) but is somewhat verbose for a single tool description. It front-loads the purpose and operations, but some details (like default page_size) could be more concise.

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?

The description covers all major aspects: operations, parameters, return format, and key data fields. Given the presence of an output schema (not shown), this is sufficient. Minor gaps include error handling details or examples, but overall it provides a complete picture for correct tool use.

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

Parameters5/5

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

The input schema has 0% description coverage, yet the description fully compensates by explaining each parameter's purpose, including nested data fields (name, unitPrice, etc.) and their types. This adds essential meaning beyond the bare 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 managing 'Products & services in Wave' and lists specific operations (Read: list, get, search; Write: create, update, archive). This is specific and helps distinguish from sibling tools like account or transaction, though it doesn't explicitly contrast with them.

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

Usage Guidelines4/5

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

The description provides clear usage context for each operation, listing required parameters (e.g., item_id for get/update/archive) and optional fields (data, query). It does not explicitly exclude use cases or name alternatives, but the structured breakdown of operations guides appropriate selection.

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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