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sample_product

Free sample rows of a product (k-anonymised where applicable) with data_through and contract version.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

The description adds behavioral context beyond the schema by mentioning k-anonymisation, data_through, and contract version. However, with no annotations, it does not disclose whether the operation is read-only, requires authentication, or what the response format looks like. The added details are useful but incomplete.

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?

The description is a single concise sentence with no wasted words. It front-loads the core action and resource. The only minor issue is that phrases like 'where applicable' and 'contract version' are vague but not verbose.

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

Completeness2/5

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

With no annotations, no output schema, and a single undocumented parameter, the description leaves out important context: when to use the tool, what the output looks like, and the meaning of 'contract version'. It is too minimal to fully guide an agent in selecting and invoking the tool correctly.

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

Parameters2/5

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

Schema description coverage is 0%, so the description carries the full burden for parameter semantics. It only implies that 'slug' identifies a product, but does not explain the slug format, how to obtain it, or any constraints. This is insufficient compensation for an undocumented parameter.

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 states a specific action ('sample rows') and resource ('product'), and it differentiates from siblings like search_products and inspect_product by focusing on sampling data rows. However, the word 'Free' is ambiguous (cost vs. sample) and the description lacks a standard verb like 'retrieve' or 'get', which slightly reduces clarity.

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?

No guidance is provided about when to use this tool versus the sibling tools. There is no mention of alternatives, conditions, or prerequisites, leaving the agent to infer usage from the tool name alone.

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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