inflation
Fetch inflation data from Alpha Vantage for economic analysis and financial planning.
Instructions
Fetch inflation
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| datatype | No |
Fetch inflation data from Alpha Vantage for economic analysis and financial planning.
Fetch inflation
| Name | Required | Description | Default |
|---|---|---|---|
| datatype | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden but only states 'Fetch inflation' without disclosing any behavioral traits. It doesn't mention if this is a read-only operation, potential rate limits, authentication needs, data freshness, or what the output looks like, leaving critical gaps for an agent.
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 extremely concise with just two words, front-loaded and zero waste. However, this brevity comes at the cost of underspecification, but purely on conciseness, it's optimal.
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?
Given the tool's complexity (economic data fetching with a parameter), lack of annotations, no output schema, and low schema coverage, the description is completely inadequate. It doesn't provide enough context for an agent to understand what the tool does, how to use it, or what to expect in return.
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 input schema has one parameter 'datatype' with 0% schema description coverage, and the description adds no information about parameters. It doesn't explain what 'datatype' means, possible values, or how it affects the inflation data fetched, failing to compensate for the lack of schema documentation.
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 'Fetch inflation' restates the tool name 'inflation' with a generic verb 'Fetch', making it tautological. It doesn't specify what type of inflation data (e.g., CPI, PPI, country, time period) or from what source, nor does it distinguish from siblings like 'cpi' which might provide similar data.
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?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools (e.g., 'cpi', 'real_gdp', 'unemployment') that might relate to economic indicators, the description offers no context, prerequisites, or comparisons to help an agent choose appropriately.
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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