Live in-date SADC deals from the PriceMate catalogue corpus (paid, $0.003/req or pass).
Real retail prices across Botswana, Lesotho, Mozambique, Namibia and South Africa:
microwaves, phones, appliances, groceries. Prices in local currency per retailer.
Args:
category: optional category filter (e.g. Electronics, Groceries, Appliances).
limit: max deals to return (1-100).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| category | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It adds cost and data scope but does not disclose response format, pagination behavior, error handling, or any side effects. The phrase 'or pass' is unclear and reduces transparency.
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 well-structured with a concise overview and an Args list. Every sentence contributes value, but the 'or pass' phrase is confusing and detracts from clarity, preventing a perfect score.
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 two-parameter query tool, the description covers the essential scope: data source, countries, categories, currency, and cost. However, it lacks any mention of result sorting, output format, or how it relates to deals_hot/deals_search, leaving advisory gaps.
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 description adds meaningful parameter details beyond the bare schema: category is illustrated with examples (Electronics, Groceries, Appliances) and limit is given a range (1-100). Since schema descriptions are absent, this compensates well for the missing schema-level documentation.
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?
Description clearly states it returns live SADC deals from a specific catalogue, with geographic scope and product categories. It distinguishes the tool as a general deals listing but does not explicitly contrast with sibling tools deals_hot or deals_search, so it misses full differentiation.
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?
No when-to-use guidance or alternatives are provided. The description does not tell the agent when to choose this over deals_hot or deals_search, and mentions cost ambiguously with 'or pass' without explaining the choice.
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.
Tools are grouped by domain (funding, deals, transcripts, etc.) and each has a specific focus: basic list, latest, search, or summary. While some pairs like deals/deals_search and funding/funding_latest could be confused, the descriptions clearly differentiate them. The boundaries are mostly clear, but the sheer number of tools requires careful reading.
Naming is inconsistent across the set. Some tools use bare nouns (funding, deals, catalogues), some use verb prefixes (get_article, list_threads, search_wire), and many use suffixes (_latest, _search, _summary). The position and style of modifiers vary between domains, making it difficult to predict tool names.
With 27 tools, the server is on the heavy end, which aligns with its terminal-style scope covering many distinct data domains (news, transcripts, funding, retail, model watch). The count is justified by the breadth, but it feels dense and could be split into smaller, more focused servers.
The server provides comprehensive coverage for most domains: listing, retrieving details, searching, and domain-specific variants (latest, hot, sentiment). Minor gaps exist, such as no way to fetch a specific funding event by ID or a latest deals tool, but these are easy workarounds.