VIA Network: Agentic Commerce

import_preference_appraisal

Import a buyer's shopping-preference appraisal (derived by a Mind from the owner's email) onto their VIA buying agent. Requires a link_token the owner minted in their VIA dashboard; it scopes the write to exactly one buyer. Pass the structured appraisal (categories, brands, sizes, cadence, budget signal). VIA never receives raw email. Taste signals shape matching and negotiation immediately; the budget signal becomes a PROPOSED spending cap that the owner must approve in the dashboard before it gates any autonomous spend.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`appraisal`	Yes	The structured shopping-preference appraisal. Use evidence_summary for prose only; never include raw quoted email.
`link_token`	Yes	The link token the buyer owner minted in their VIA dashboard (POST /api/buyer/[buyerId]/appraisal action=mint_link).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedJul 27, 2026

TDQS

A4.7/5.0

Behavior5/5

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

No annotations are provided, so the description fully carries the burden. It discloses that VIA never receives raw email, taste signals immediately affect matching, and the budget signal becomes a proposed cap requiring approval. This covers safety, privacy, and post-import behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Five sentences, each adding essential context without redundancy. The main action is front-loaded, and every sentence earns its place.

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

Completeness5/5

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

For a 2-param tool with nested objects and no output schema, the description covers prerequisites, data structure, privacy, and behavioral effects. No gaps identified.

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?

Schema coverage is 100%, but the description adds value by clarifying that evidence_summary is for prose only and never raw email, and explaining the effect of budget_signal. The description also reiterates the link_token requirement.

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 clearly states the tool imports a buyer's shopping-preference appraisal onto their VIA buying agent, specifying the source (Mind from email) and target. It distinguishes from siblings like get_buyer_preferences by focusing on import rather than read.

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?

The description explains the prerequisite (link_token minted by owner) and scoping to exactly one buyer. It also describes the privacy policy (no raw email). It does not explicitly say when not to use, but context is 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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TDQS

A3.9/5.0

Disambiguation4/5

Most tools have clearly distinct purposes (discovery, purchasing, negotiation, seller management, taste/intent). Some overlap exists, e.g., multiple ways to get product details, but descriptions clarify distinct use cases. A few tools like find_buyers and get_buyer_briefs might be confused at first glance but have different inputs.

Naming Consistency4/5

Tool names predominantly follow verb_noun pattern in snake_case, e.g., find_seller, buy_product, get_shipping_quote. The outlier is seller_mcp_url which starts with a noun instead of a verb, and negotiate is a bare verb but fits. Overall consistent with minor deviations.

Tool Count3/5

28 tools is on the high side for a single server, but the domain is complex (agentic commerce covering discovery, purchasing, negotiation, seller registration, etc.). The count is borderline heavy but reasonable for the breadth of functionality.

Completeness4/5

The tool set covers major aspects of agentic commerce: search, buying, negotiation, shipping, digital delivery, seller onboarding, and taste/intent. Missing features like order tracking or store updates are minor gaps; core workflows are well-supported.

Resources

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