shopify_bulk_query

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

Annotations provide readOnlyHint=true and openWorldHint=true, but the description significantly expands on behavioral details: async execution, background processing, JSONL output, restrictions (connection limits, depth limits, id requirement), and API version-specific concurrency limits. This goes well beyond the annotations, giving agents a full picture of what to expect.

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

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

The description is concise and well-structured, front-loading the core purpose and usage context. The restrictions are clearly bullet-listed, and the Args section is logically placed. No redundant sentences; every sentence adds value. Minor deduction for not being even more streamlined, but it's appropriately sized given the complexity.

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

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

Given the tool's complexity (async, multiple restrictions, API version nuances), the description covers all critical aspects: purpose, usage, restrictions, return type (BulkOperation ID), and how to proceed (poll). The output schema likely describes the return structure, so not detailing the response format is acceptable. Sibling tools are distinct and the description clearly differentiates them.

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

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

The input schema has 3 parameters with 0% description coverage; however, the description's 'Args' section provides meaningful context for each: 'query' is described as a read-only GraphQL document with a single root connection, 'shop' is clarified as a store alias or domain required when multiple stores are configured, and 'api_version' is noted as an override with a default. This adds value beyond the schema's type-only information, but could be even more explicit (e.g., format for query).

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

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

The description clearly states the tool's purpose: launching an async bulk export of a read-only GraphQL query. It distinguishes itself from siblings by specifying it is for large datasets where paginated queries become impractical and explicitly mentions polling with shopify_bulk_poll for results. The verb 'launch' and resource 'async bulk export of a read-only GraphQL query' are specific and non-ambiguous.

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

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

Provides explicit usage guidance: use when exporting datasets too large for paginated queries (>10k records or hundreds of pages). It also contrasts with 'normal' queries implicitly by referencing pagination alternatives. While it doesn't explicitly name shopify_graphql_query for smaller queries, the mention of 'paginated queries' serves as a clear alternative. Restrictions are thoroughly listed, aiding correct invocation.

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