Get what's trending right now in human culture. Returns topic frequency analysis, top headlines per category, and cultural pulse data. Perfect for agents that need to stay current.
| Name | Required | Description | Default |
|---|---|---|---|
| timeframe | No | Time window for trending analysis | this_week |
| agent_token | No | Credential from register_agent. Alternative to Authorization: Bearer. Never put it in URLs. |
Changes observed during successful MCP inspections.
Input schema / properties / agent_tokenAdded value: +{
+ "description": "Credential from register_agent. Alternative to Authorization: Bearer. Never put it in URLs.",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint true and destructiveHint false, so the safety profile is covered. The description adds some context about what the tool returns, but it does not reveal behavioral details such as update latency, output volume, or how 'trending' is determined. It does not contradict the annotations.
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 sentences with the core purpose front-loaded and the rest describing what is returned and who should use it. The phrase 'cultural pulse data' is somewhat vague, but the description is compact and has no significant waste.
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?
With zero required parameters and annotations covering safety, the tool is easy to invoke correctly. The description names three return components, which is helpful since there is no output schema. It could be stronger by defining what 'cultural pulse data' means or clarifying categories, but it is sufficient for an agent to understand the general 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?
Schema description coverage is 100%, and the schema provides rich meaning for both parameters: timeframe has an enum and default, and agent_token includes credential source and usage warnings. The description adds no parameter-level detail, but with full schema coverage this is acceptable.
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 states a specific action ('Get what's trending right now in human culture') and enumerates return contents: topic frequency analysis, top headlines per category, and cultural pulse data. This is clear, but it does not explicitly distinguish itself from sibling tools like get_culture_news.
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 phrase 'Perfect for agents that need to stay current' gives a general use case, but it does not explain when to choose this tool over get_culture_news or generate_digest, nor does it mention exclusions. Usage context is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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