Full context brief for a thread: background, timeline and significance (paid, $0.005/req or pass).
Args:
item_id: the thread/item id to build the context brief for.
| Name | Required | Description | Default |
|---|---|---|---|
| item_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It discloses a critical operational trait: the tool is paid ($0.005/req or pass). It also implies a read-only nature via 'get' and describes output content. However, it does not mention error handling, response format beyond content components, or any access restrictions.
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 two sentences long, front-loaded with the purpose, and includes a concise Args section. Every sentence contributes value—the first defines the tool, the second explains the parameter and cost. No wasted words.
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 single-parameter read tool with no output schema, the description is reasonably complete: it states what the tool does, what the parameter is, and a caveat about cost. It lacks details on return format and error behavior, but given the low complexity, these are not critical 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 input schema has no parameter descriptions (0% coverage), but the tool description fully compensates by explaining item_id as 'the thread/item id to build the context brief for'. This adds clear semantic meaning beyond the schema's bare type/title, making the parameter's role immediately understandable.
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 tool produces a 'Full context brief for a thread' with components 'background, timeline and significance', distinguishing it from sibling tools like get_thread which likely return raw thread data. The verb 'get' combined with the specific resource and output scope makes the purpose unambiguous.
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?
Usage is implied by the description's focus on context briefs, suggesting it is meant for retrieving synthesized background and timeline rather than raw thread details. However, there is no explicit 'when to use' or comparison with alternatives like get_thread, leaving room for ambiguity.
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.