Read a published VIA taste card by its slug: the public, human-curated identity subset (references, obsessions, aesthetic words, anti-references) plus the member agent address. Cards are shared by their owners; there is no directory or search. Returns not_published for unknown or unpublished slugs.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The card slug from a shared link, e.g. app.getvia.xyz/taste/<slug>. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description appropriately discloses that it is a read operation and indicates the return behavior for unknown/published slugs. No other side effects or auth requirements are needed given the tool's nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words; the purpose is front-loaded and clearly communicated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with one parameter and no output schema, the description fully explains the return values and the resource structure, providing sufficient context for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the single parameter with 100% description coverage. The description adds context by explaining where the slug comes from (shared link example), which aids correct usage beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Read a published VIA taste card by its slug') and specifies the resource and its contents, distinguishing it from sibling tools like get_store_card.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description notes that cards are shared by owners and there is no directory, implying when to use (when you have a slug). However, it does not explicitly mention when not to use or suggest alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.
