List GDELT Television 2.0 AI concept entities. Access GDELT's catalog of Google Knowledge Graph concepts, with an optional limit for most frequent entries.
List GDELT Television 2.0 AI concept entities. Return GDELT's own catalog of Google Knowledge Graph concept.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum entries to return, most-frequent first. |
Changes observed during successful MCP inspections.
v1.16.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool lists a catalog, but it does not disclose ordering behavior beyond the optional limit parameter, pagination, whether results are static or dynamic, or what fields each returned concept entity contains.
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 compact and front-loaded with the core purpose ('List GDELT Television 2.0 AI concept entities'). It wastes little space, though the trailing fragment 'Return GDELT's own catalog of Google Knowledge Graph concept.' is slightly awkward and adds limited information.
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 lacks an output schema and annotations, so the description must explain what the response looks like and how to use the tool. It does not describe the returned data shape, field names, or how the catalog relates to TV searches, leaving an agent with insufficient information to confidently parse or use the result.
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?
Although the schema already covers the limit parameter at 100%, the description adds value by stating this is a catalog listing and that the optional limit caps returned entries; it also notes most-frequent-first ordering, which is meaningful behavior beyond a bare schema definition. The single optional parameter is well explained.
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 a specific verb and resource ('List GDELT Television 2.0 AI concept entities') and describes what the tool returns (a catalog of Google Knowledge Graph concepts). However, it does not explicitly distinguish itself from the similarly named sibling gdelt_tv_visual_entities, and the grammar of the trailing fragment is incomplete.
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 implies this is a read-only catalog listing for GDELT TV concept entities, but it provides no explicit guidance on when to choose this over gdelt_tv_visual_entities or other GDELT TV tools. An agent can infer some usage context, but there are no stated exclusions or alternative routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.