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veroq_economy_indicator

Retrieve historical data and current values for specific economic indicators from FRED to analyze trends and make informed decisions.

Instructions

Get a specific FRED economic indicator with historical observations.

WHEN TO USE: For detailed history of one indicator. Use veroq_economy (no args) for a summary of all indicators. RETURNS: Series info (ID, frequency, units), latest value, and historical observations array. COST: 2 credits. EXAMPLE: { "indicator": "fed_funds", "limit": 24 } CONSTRAINTS: Max 100 observations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indicatorYesIndicator slug (e.g. gdp, cpi, unemployment, fed_funds, retail_sales, housing_starts)
limitNoNumber of historical observations to return (default 30, max 100)
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. Discloses cost ('2 credits'), return structure ('Series info, latest value, and historical observations array'), and operational constraints ('Max 100 observations'). Lacks error handling or rate limit details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Uses structured section headers (WHEN TO USE, RETURNS, COST, EXAMPLE, CONSTRAINTS) for scannability. Every line provides distinct information (purpose, sibling differentiation, cost, example, limits). Zero redundant text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Compensates for missing output schema by detailing return structure (series metadata, latest value, observations array). Establishes FRED data source context. Could enhance further by mentioning data frequency limitations or lag times, but adequate for tool complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, establishing baseline 3. Description adds value via concrete JSON example showing expected indicator slug format ('fed_funds') and reinforces the 'limit' parameter constraint (max 100). Contextualizes 'indicator' parameter as FRED-specific.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with specific verb ('Get') + resource ('FRED economic indicator') + scope ('historical observations'). Explicitly distinguishes from sibling tool 'veroq_economy' by contrasting detailed single-indicator history vs. summary of all indicators.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Contains explicit 'WHEN TO USE' section stating 'For detailed history of one indicator' and names specific alternative 'veroq_economy (no args)' for summary use cases. Clear differentiation between detailed vs. broad economic data retrieval.

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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