Lists all 8 collectible FRED datasets, helping you identify which economic data series are available for retrieval.
列出所有可采集的 FRED 数据集（共8个）
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool lists all collectible FRED datasets, which implies a non-destructive read operation, but it does not explicitly disclose side effects or confirm read-only behavior. For a simple list tool this is adequate but minimal.
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, front-loaded sentence conveys the essential information without any wasted words. It states the action, target, scope, and quantity with high efficiency.
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 zero-parameter listing tool with an output schema present, the description is sufficiently complete. It could optionally mention how the results relate to fred_data (e.g., using returned identifiers), but this is not critical for calling the 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 tool has 0 parameters and the schema is empty, so parameter ambiguity is nonexistent. Per the rubric, 0 parameters earns a baseline of 4; the description adds no parameter-specific detail because none is needed.
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 ('列出') and resource ('可采集的 FRED 数据集') and even states the exact count (8), making the tool's scope immediately clear. It distinguishes itself from sibling tools like fred_data or wb_list by specifying FRED datasets and the 'collectible' qualifier.
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 a discovery/catalog use case (listing available datasets), but it does not explicitly state when to use this tool versus alternatives like fred_data or wb_list. There is no direct mention of 'use this to get dataset IDs before calling fred_data', so guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.