Get full details for a single POPS4 product including description, pricing, care instructions, occasion tags, and links to virtual proof page where the buyer can see their logo on the product.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Product slug (from search results) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the burden of behavioral disclosure. The verb 'Get' suggests a read-only operation, and the description lists the return contents. However, it does not explicitly confirm no side effects, mention permissions, or discuss error/not-found behavior, which would be valuable given the absence of annotations.
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?
The description is a single, well-structured sentence that front-loads the key purpose ('Get full details for a single POPS4 product') and then enumerates the specific data points. Every word adds value with no filler.
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 getter with a single parameter and no output schema, the description provides a good summary of expected content (description, pricing, care instructions, occasion tags, virtual proof page link). It could be slightly more explicit about the shape of the response or potential edge cases, but overall it is adequately complete for the tool's simplicity.
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?
Schema coverage is 100% because the only parameter, 'slug', has a description indicating it comes from search results. The tool description itself adds no additional parameter semantics beyond what the schema provides, so a baseline of 3 is appropriate.
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 uses a specific verb ('Get') plus resource ('single POPS4 product') and enumerates the exact details returned. It clearly distinguishes itself from sibling tools like search_products or get_product_catalog by focusing on a single product's full details.
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 implies usage context ('single product') and the schema param description mentions 'from search results', so an agent can infer this tool is for fetching details after searching. However, it does not explicitly state when to use this versus alternatives like get_product_catalog or get_live_quote.
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.
get_quote and get_live_quote both return wholesale quotes for product SKUs and quantities, differing only in context (enterprise events vs. general). get_product_catalog and search_products both search the catalog with filters, making the boundary between them unclear. These overlaps can lead to agent misselection.
All tools use snake_case with a verb_noun pattern (get_, generate_, search_, track_). There are minor deviations where similar actions use different verbs (e.g., get_product_catalog vs. search_products, get_quote vs. get_live_quote), but the overall pattern is consistent and predictable.
With 10 tools, the server is well-scoped for its purpose. Each tool covers a distinct aspect of the procurement and event management domain, and the count falls within the ideal 3-15 range, earning its place without feeling bloated.
The server covers product discovery, catalog browsing, quotes, event program generation, and shipment tracking. However, there is no tool for placing an order or managing event records, and the link between quotes and orders is unclear, leaving notable gaps in the end-to-end procurement workflow.