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Url Handle

url_handle
Read-onlyIdempotent

Turn a product title into a valid, unique Shopify URL handle. FREE.

Shopify handles are lowercase, may contain letters, numbers and dashes, and may not contain spaces. Typical input {"title": "Men's Merino Wool Socks (2-Pack)"} returns {"handle": "mens-merino-wool-socks-2-pack", "valid": true, "changed": true, "collisions": []}.

Use when generating handles for an import, or checking one you already have. Not for validating a whole header row: that is product_csv_check. Errors: on invalid, missing, or malformed input this tool never raises a protocol error; it returns {"error": ""} (for example {"error": "title must not be empty"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input Schema

NameRequiredDescriptionDefault
titleYesThe product title or a candidate handle, e.g. "Men's Merino Wool Socks".
existingNoHandles already used in the store or the file, so a collision can be reported and a suffixed alternative suggested. Optional.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, and the description redundantly restates read-only/idempotent plus 'FREE'. It does add genuine value beyond annotations, though, with an explicit error contract: no protocol errors are raised; failures come back as {"error": ...} with a fix hint, and retry is always safe.

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?

Purpose and the worked example are front-loaded, and the alternative-tool routing and error contract follow logically. Some sentences repeat annotation content ('read-only and idempotent') and the 'FREE.' fragment is marketing noise that earns no place.

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

Completeness5/5

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

For a 2-parameter tool with an output schema and full annotation coverage, the description covers purpose, scope boundary, example I/O and error behavior. An agent has everything needed to call it correctly and interpret failures.

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 both parameters are already documented, including the candidate-handle interpretation of 'title' and the collision-reporting role of 'existing'. The description's typical-input example reinforces this but does not name the 'existing' parameter or explain collision handling beyond what the schema states, so baseline 3 applies.

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?

States a specific verb and resource: turns a product title into a valid, unique Shopify handle, and names the exact transformation rules (lowercase, letters/numbers/dashes, no spaces). The worked input/output example makes the operation unambiguous and separates it from sibling tools like product_csv_check.

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

Usage Guidelines5/5

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

Explicitly gives both when-to-use cases (generating handles for an import, checking an existing one) and an explicit when-not case routed to a named sibling: 'Not for validating a whole header row: that is product_csv_check.' Nothing is left to inference.

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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