Search 368 episodes of a business/finance podcast corpus (paid, $0.002/req or pass).
FTS-ranked segments with episode id, date and start time. Ideal for
research agents that need quoted, dated business-news material.
Args:
q: search term, at least 3 characters (e.g. "stablecoin", "agentic payments").
limit: max results (1-20).
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | ||
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the behavioral disclosure burden. It discloses the cost per request, the minimum query length, and FTS ranking. However, it does not discuss read-only guarantees, error behavior, or how results are sorted beyond 'FTS-ranked', leaving some gaps.
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 concise and well-structured: a clear opening sentence, a sentence on output details, a usage note, and a compact args list. Every sentence earns its place without fluff or redundancy.
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 search tool with no output schema, the description covers the essentials: purpose, output fields, cost, and parameter constraints. It doesn't explain how to chain with sibling tools (e.g., transcripts_context), but that is not strictly required for invoking this tool correctly.
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 has 0% description coverage, so the description fully compensates by documenting 'q' with a length requirement and examples, and 'limit' with a range. This adds significant meaning beyond the schema, though it could be even more explicit about default behavior or optionality.
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 searches a podcast corpus, with a specific verb and resource. It mentions FTS-ranked segments and result fields, distinguishing it from single-episode fetchers. However, it doesn't explicitly compare to siblings like transcripts_episode, which would fully satisfy the 'distinguishes from siblings' criterion.
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 provides a clear use case: 'Ideal for research agents that need quoted, dated business-news material.' This gives context on when to use the tool, but it does not mention when not to use it or explicitly name alternative tools, stopping short of a full 5.
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.