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Tendrils — live commerce tools for AI agents

get_product_details

Fetch full technical specifications, parsed dimensions, materials, care instructions, and variant matrix for a product.

Input Schema

NameRequiredDescriptionDefault
handleNoThe Shopify product URL handle (e.g., 'tess-3-piece-sleeper-sectional')
product_idNoThe Shopify Product ID (e.g., 'gid://shopify/Product/5826780551' or numeric ID)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full disclosure burden, and it leaves key behavior unstated. It never says that at least one of handle or product_id must be supplied (the schema marks zero required parameters), whether one identifier takes precedence over the other, or what happens when a product is not found.

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?

A single well-formed sentence with the payload contents front-loaded and no filler. It is efficient, though the comma-separated field list is dense and gives no routing information to accompany it.

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

Completeness3/5

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

With no annotations and no output schema, the description usefully enumerates what the response contains, which partly substitutes for a return-value spec. It is still incomplete for a lookup tool with two optional identifiers, since the invocation rule (supply a handle or an ID) and failure behavior are absent.

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%, with both parameters documented and example values given, so the baseline of 3 applies. The description adds no meaning beyond the schema, and notably does not resolve the ambiguity of two optional identifiers — it never says which to prefer or whether they may be combined.

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

Purpose4/5

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

The description gives a specific verb ('Fetch') and a precise inventory of the resource contents: technical specifications, parsed dimensions, materials, care instructions, and variant matrix. That is far more informative than a bare 'get product'. It does not, however, distinguish itself from siblings such as get_product_ar_model or compare_products_deep_matrix, so it falls short of a 5.

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?

There is no statement of when to use this tool versus the ten sibling tools, no prerequisites, and no exclusions. The only implicit signal is that 'full technical specifications' suggests a deep-detail lookup, but the agent must infer that on its own.

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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