transcripts_sentiment
Lexicon sentiment over top matching segments (paid, $0.002/req or pass).
Args:
q: search term.
limit: max segments scored (1-20).
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | ||
| limit | No |
terminal
TDQS
B3.2/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden. It discloses that the tool is paid and includes a 'pass' option, but the meaning of 'or pass' is ambiguous. It also does not mention response format, authentication, or rate limits, leaving significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, with the core purpose in the first line and parameter explanations in a list. Every sentence earns its place, and it is well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-like tool with 2 parameters and no output schema, the description provides basic invocation information such as cost and limits. However, it lacks details about the return format or error behavior, which is important without an output schema, so it is only partially complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description compensates by explaining both parameters: 'q: search term' and 'limit: max segments scored (1-20)'. This adds clear semantic meaning beyond the schema's type/default information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Lexicon sentiment over top matching segments' which clearly identifies the tool's function as computing sentiment scores for segments matching a search query. It is distinguishable from sibling transcripts tools by its focus on sentiment, though it lacks an explicit imperative verb.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like transcripts_search or transcripts_context. The cost note ('paid, $0.002/req or pass') is a usage consideration but does not help with tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Try in Browser
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
B3.3/5.0
Disambiguation4/5
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 Consistency2/5
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.
Tool Count3/5
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.
Completeness4/5
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.