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Product Aura

List platform packs

list_packs
Read-onlyIdempotent

Lists the platform packs (Amazon, A+, Etsy, Shopify, social ads) with their shots, credit cost per shot, the recipes per pack (shot or module lists per product type), the supported languages for text on images, and the prices: plans monthly or yearly (20% off, a year of credits up front) with their credits, brand kits and credit-pack discount, and one-time credit packs (valid 24 months). Free; no account needed.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world, so the safety profile is covered. The description adds useful context beyond that: the call is free and requires no account. It does not disclose response shape or size, which matters for a tool that apparently aggregates packs, recipes, languages, and multiple pricing structures.

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 dense sentence front-loads the verb and resource, then enumerates contents and pricing details. The parenthetical pricing clauses (20% off, credits up front, 24-month validity) are business detail that could arguably be trimmed, but they are informative rather than filler.

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?

No output schema exists, so the description carries the burden of describing return values, and it does so at a category level only, with no structure, nesting, or size hints. For a zero-parameter read tool with full annotation coverage this is adequate, but an agent cannot anticipate the response's organization.

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

Parameters4/5

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

Zero parameters, so the baseline of 4 applies. The description instead explains what the returned data contains, which is the relevant semantics for a no-input listing tool.

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?

States a specific verb and resource ('Lists the platform packs') and enumerates the concrete contents returned: shots, credit cost per shot, recipes, supported languages, and pricing tiers. An agent can tell this is a catalog/pricing discovery tool, distinct from transactional siblings like buy_credits or get_credit_balance, though it never names those alternatives.

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

Usage Guidelines4/5

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

Adds clear context markers: 'Free; no account needed', which signals it is safe to call before any purchase or signup decision. It does not explicitly say when to prefer this over answer_facts or estimate_cost, but the catalog-listing scope makes the intended entry point reasonably clear.

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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