list_topics
List all topics and series (names are Chinese, e.g. 人工智能 = AI, 投资 = investing, 加密与 Web3 = crypto) with episode counts.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
List all topics and series (names are Chinese, e.g. 人工智能 = AI, 投资 = investing, 加密与 Web3 = crypto) with episode counts.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=false), but the description adds two genuinely useful behavioral facts: the response carries episode counts per topic, and topic names are Chinese rather than English, which materially affects how an agent matches user queries.
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?
A single sentence, front-loaded with the core action, and the parenthetical examples are short and earn their place by preempting the Chinese-name confusion.
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 no parameters and no output schema, the description covers the essentials: what is listed and that counts come back. Minor omissions such as ordering or whether the list is exhaustive for a closed-world corpus are not addressed.
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 tool takes zero parameters, so there is nothing for the description to clarify beyond what the empty schema already conveys; the baseline of 4 applies.
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 uses a specific verb and resource ("List all topics and series") and explicitly states the payload includes episode counts. It doesn't name the sibling tools it complements (search_episodes, list_people), so it falls just short of full sibling differentiation.
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 only implied: an agent can infer this is the discovery step before searching or fetching episodes, but the description never says when to call this versus search_episodes or list_people, nor does it state any prerequisites.
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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