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Product price history and call

get_product
Read-onlyIdempotent

Full detail for one tracked product by slug: community sentiment, reference price and basis, date of the latest price observation, portafilter size (machines) or accessory size (sized accessories), superautomatic / manual-lever / hand-grinder flags, product URL and Amazon link.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesA slug from search_catalog.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare read-only, idempotent, non-destructive, and closed-world behavior, so the description need not repeat safety. It does add the fact that this returns 'full detail' for a tracked product and lists the returned fields, which is useful context beyond annotations, but it omits any behavioral notes like caching or error handling. With annotations covering the safety profile, a 3 is appropriate.

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, front-loaded sentence that efficiently lists the returned fields. It is dense but not bloated; every phrase earns its place by specifying a distinct piece of returned data.

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 read-only lookup tool with full schema coverage and annotations, the description is nearly complete: it tells what the tool returns and implies it retrieves a single product by slug. It falls short only by not clarifying how this differs from search_catalog or when to prefer it, but that is minor given the simple contract.

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 coverage is 100% – the single 'slug' parameter is fully described in the schema, including its origin from search_catalog. The description adds no parameter details beyond what the schema provides, so baseline 3 is correct.

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 names a specific verb (retrieves) and resource (one tracked product), and then enumerates the exact fields returned: sentiment, price, date, size, flags, URLs. This is precise enough that an agent immediately knows what it gets.

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 guidance on when to use this tool versus siblings like search_catalog (for finding slugs) or watch_price (for setting alerts). The schema hints 'slug from search_catalog', but the description itself gives no usage context or exclusions.

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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