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hvkshetry

inventree-mcp

by hvkshetry

barcode

Scan barcodes to look up items or assign barcodes to inventory objects like parts, stock, and orders.

Instructions

Barcode scanning and assignment in InvenTree.

Operations: Read: scan, lookup Write: assign, unassign

Args: operation: One of the operations listed above. barcode_data: Barcode string for scan/assign/lookup. model_type: Model type for assign/unassign (part, stockitem, stocklocation, build, purchaseorder, salesorder, returnorder). pk: Object ID for assign/unassign.

Returns: JSON string with barcode result or {"error": "..."}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
operationYes
barcode_dataNo
model_typeNo
pkNo

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 and destructiveHint=false; the description adds the specific write operations (assign/unassign) but discloses no additional behavioral traits such as side effects, authentication needs, or rate limits. With annotations present, the description provides only marginal extra context.

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 concise (roughly 6 lines), front-loads the overall purpose, then lists operations, parameter details, and return format. Every sentence adds value with no repetition or fluff.

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 tool with 4 parameters (0% schema coverage), minimal annotations, and an existing output schema, the description covers purpose, operations, parameter details, and return format. It lacks prerequisites or error handling specifics but is largely complete for typical 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?

Schema description coverage is 0%, so the description fully compensates by clearly explaining each parameter: operation (enumerates options), barcode_data (purpose), model_type (lists valid models like part, stockitem, etc.), and pk (object ID). 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.

Purpose5/5

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

The description clearly states 'Barcode scanning and assignment in InvenTree' and lists specific operations (scan, lookup, assign, unassign), providing a precise verb+resource combination that distinguishes this tool from siblings like 'part' or 'stock'.

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

Usage Guidelines3/5

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

The description implies usage for barcode-related tasks but does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or when-not-to-use guidance. No sibling differentiation beyond the tool's name.

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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