Latest Monexus Terminal wire items (paid, $0.001/req or pass).
Args:
category: optional beat filter, e.g. geopolitics, business, tech, crypto, sports, science.
query: optional full-text search string.
limit: max items to return (1-100).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No | ||
| category | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool is paid ($0.001/req or pass), which is valuable beyond the schema. However, it does not state whether this is a read-only operation, how results are ordered, or what happens when no filters are provided (beyond returning latest). Without annotations, this leaves some behavioral ambiguity, but the cost disclosure earns a middle score.
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 short sentences plus a list of args. Every piece of information is useful and directly relevant. The description is efficient and well-structured.
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?
The tool has no output schema, so the description should ideally describe the return shape. It does not, nor does it mention ordering or edge cases. However, it does cover purpose and all parameters. For a simple search tool, this is adequate but not fully complete.
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?
All three parameters are explained in the description with specific semantics: category as a beat filter with examples, query as full-text search, limit with a range (1-100). The schema has no descriptions (0% coverage), so the description fully compensates and adds constraints not present in the schema.
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 identifies the tool as retrieving the latest wire items from Monexus Terminal, with optional filters. The name 'search_wire' and the description align, distinguishing it from article/thread siblings by resource type. However, it lacks an explicit verb like 'searches' or 'retrieves' in the description, relying on the tool name for the action.
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 mention of when to use this tool versus the sibling tools. It does not state that it is for wire items only or that alternatives exist for articles/threads. The description provides no contextual guidance on selection.
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.