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Glama

add_registry_item

Add a product to your Zola registry by SKU, with options for quantity, most-wanted status, and group gifting.

Instructions

Add a product (by SKU) to the registry. If collection_id is omitted, the default collection is looked up automatically.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sku_idYesProduct SKU ID (e.g., from search_registry_products)
quantityNoDefault 1
most_wantedNoMark as a most-wanted gift. Default false
collection_idNoCollection to add into; defaults to the registry's default collection
enable_group_giftingNoAllow multiple guests to chip in. Default false

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2.0.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observedv1.4.2

TDQS

B3.4/5.0
Behavior2/5

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

Annotations only provide destructiveHint: false, which is minimal. The description adds the default-collection lookup behavior, but this largely repeats the collection_id parameter schema. It does not disclose whether adding an already-present SKU is idempotent, what happens if the SKU is invalid, or what the tool returns after a successful add.

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, tightly worded sentence with no filler. The core action is front-loaded, and the only conditional detail — default collection lookup — is relevant and expressed efficiently.

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 straightforward add operation with a fully documented schema, the description is reasonably complete. It states the action, the identifier type, and the key default behavior. It does not discuss errors or return values, but the absence of an output schema and the simplicity of the operation make this only a minor gap.

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 description coverage is 100%, so the schema fully documents all five parameters. The description adds little parameter meaning beyond the schema; it just confirms the SKU is used to identify the product and that collection_id defaults. Baseline 3 is appropriate.

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 states a specific verb and resource: "Add a product (by SKU) to the registry." This clearly differentiates it from sibling tools like update_registry_item, remove_registry_item, and search_registry_products, all of which act on registry items but are distinct actions.

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 gives no explicit guidance on when to choose this tool over alternatives like update_registry_item or remove_registry_item. It implies usage by its action verb, but does not state prerequisites, exclusions, or conditions under which a sibling tool would be more appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.