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Glama

Edit a department

dept_edit
Idempotent

Edit an existing department/category by its ID. All fields are optional except the ID. Use data_list_departments to find the department ID first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesID of the department to modify
priceNoDefault price for free-price items
stockNoStock quantity override at department level
titleNoDepartment/category display name
vatIDNoDefault VAT rate ID for this department
unitIDNoUnit of measure ID
positionNoDisplay order on keyboard
shopHideNo1 to hide from online shop
needPrepaNo1 if items require kitchen preparation
discountIDNoDefault discount ID
eatinvatIDNoEat-in VAT rate ID
shortTitleNoShort label for receipt or keyboard
deptGroupIDNoDepartment group this department belongs to
activityCodeNoAccounting activity code
keyboardHideNo1 to hide from POS keyboard
variationID0NoVariation type ID for slot 0
variationID1NoVariation type ID for slot 1
variationID2NoVariation type ID for slot 2
variationID3NoVariation type ID for slot 3
variationID4NoVariation type ID for slot 4

TDQS

A4.2/5.0
Behavior4/5

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

Description adds 'All fields are optional except the ID' beyond annotations (idempotentHint=true, destructiveHint=false). Annotations already indicate non-destructive and idempotent behavior, so description provides useful additional constraint on parameter usage.

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?

Two sentences, front-loaded with main action, no unnecessary words. Efficiently covers purpose, parameters, and prerequisite.

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?

With 20 parameters, high schema coverage, and clear description of required ID and prerequisite step, the description is sufficient for correct tool usage. No output schema, but not needed for this mutation tool.

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 100% with each parameter described. Description reinforces that id is required and others optional, adding marginal value. Baseline 3 is appropriate as schema already handles parameter explanations.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states tool edits an existing department by ID, with verb 'edit' and resource 'department/category'. It distinguishes from siblings like dept_add and dept_delete by focusing on editing existing records.

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?

Explicitly instructs to use data_list_departments to find the department ID first, providing a prerequisite step. Does not mention alternatives but context implies differentiation from add/delete tools.

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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TDQS

A3.7/5.0
Disambiguation5/5

Each tool targets a distinct entity or action (account, client, order, product, payment, VAT, etc.), with clear naming like 'account_create' vs 'account_edit' and 'data_list_' prefixed listings. No overlapping purposes detected.

Naming Consistency5/5

All tool names use snake_case and follow a consistent verb_noun pattern (e.g., account_create, client_add, data_list_clients). Even compound names like auth_login_with_otp adhere to this structure.

Tool Count4/5

41 tools is high but justified by the wide scope of a POS/accounting system (accounts, clients, orders, products, payments, VAT, reports). Slightly above the typical range but well-scoped.

Completeness5/5

The tool surface covers CRUD for all major entities (clients, departments, products, VAT, payment modes, orders), plus queries, reports, and authentication. No obvious gaps for a small business management server.

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