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AIBuilder Marketplace: software pricing dossiers

get_product

Read-onlyIdempotent

The full record for one product: plans, every cost trap with its full evidence sentence, pricing date, unknowns, own hands-on observations in measured (claims, exit-test scope and three-valued facts with dates and review links), price rules if any, and the vendor handoff with affiliate disclosure.

Input Schema

NameRequiredDescriptionDefault
product_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety bar is met. The description adds genuinely useful context beyond that: results carry full evidence sentences, explicit 'unknowns', and an affiliate disclosure on the vendor handoff — the last being a material trust signal an agent would not otherwise know to watch for. It stops short of noting payload size or behavior for an unknown product_id.

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?

One front-loaded sentence that leads with the core purpose before listing contents, so an agent can stop reading early. The content list is dense and slightly run-on ('in measured (claims, exit-test scope and three-valued facts...'), costing some readability without wasting whole sentences.

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?

With no output schema, the description appropriately carries the burden of describing return contents in detail, including evidence, unknowns, observations and handoff data. Remaining gaps — where product_id comes from, and what happens on an unknown id — are minor for a single-key read tool.

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% and the single parameter product_id has no title detail, yet the description says nothing about the identifier's format or provenance (e.g., an id returned by search_products). With one parameter the gap is small, but the description does no compensating work here.

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?

Opens with a concrete verb+resource framing ('The full record for one product') and then enumerates the record's contents, which lets an agent separate it from siblings like get_evidence (evidence only) and compare_products (multi-product). It never states the retrieval key explicitly, but 'for one product' combined with the required product_id is unambiguous.

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 call this versus alternatives: nothing says to fetch a product_id from search_products first, nor when to prefer get_evidence for a single trap or build_purchase_dossier for a decision. The agent must infer routing from the content list 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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