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Glama

Crypto Data & Market Analysis Agent

get_economic_calendar

Read-onlyIdempotent

Scheduled macro events (CPI, PCE, NFP / Employment Situation, GDP, Retail Sales, FOMC) from the official US release calendar. Call for upcoming economic catalysts. Returns the scheduled date and indicator, not analyst consensus.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoHow many days ahead to cover, defaults to 14

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesScheduled macro releases ahead, soonest first.

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description's burden is lower. It adds behavioral context by stating the return includes scheduled date and indicator (not consensus), which is useful but does not disclose data freshness or scope limitations beyond 'US release calendar.'

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

Conciseness4/5

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

The description is concise at two sentences, front-loading the key events list and purpose. Every clause adds value, though the structure could be slightly improved by separating the return type more explicitly from the usage guidance.

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?

For a simple tool with one optional parameter and an output schema, the description covers its core purpose, input range, and what it returns (scheduled date and indicator). It explicitly notes it does not return consensus, which is helpful. Missing a brief note on data source limitations (US-only) is a minor gap.

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

Parameters3/5

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

Schema coverage is 100%, and the single parameter 'days' is well-described in the schema with default and purpose. The description adds no additional semantic information about the parameter, meeting the baseline but not exceeding it.

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?

The description clearly states the tool retrieves scheduled macro events (CPI, PCE, NFP, GDP, Retail Sales, FOMC) from the official US release calendar. It provides specific examples and distinguishes from sibling tools like get_macro_rates by focusing on event dates rather than rate data.

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

Usage Guidelines3/5

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

The description advises calling for 'upcoming economic catalysts,' giving clear context for when to use the tool. However, it does not mention when not to use it or explicitly compare to siblings like get_macro_rates, leaving some situational guidance implicit.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct data domain—network health, market prices, news, DeFi, derivatives per-venue vs aggregate, economic calendar, ETH address, whale flows, execution cost, sentiment, implied volatility, macro rates, market brief, dominance, history, and traditional market quotes. The only similar pair (get_derivatives vs get_derivatives_aggregate) is clearly differentiated by level of detail, so there is no real ambiguity.

Naming Consistency5/5

All tools follow the get_<domain> pattern with descriptive noun phrases (e.g., get_btc_network, get_eth_whale_flows, get_market_brief). No mixed verb styles or casing conventions appear, making the naming fully predictable and consistent.

Tool Count4/5

At 17 tools, the surface is slightly above the ideal 3-15 range, but the breadth of the domain—spot, derivatives, on-chain, macro, sentiment, and execution—justifies each tool. It's borderline but each tool earns its place in a comprehensive market analysis agent.

Completeness5/5

The toolset covers nearly every major facet of crypto market analysis: prices, history, dominance, derivatives, on-chain activity, DeFi, macro, economic calendar, sentiment, implied volatility, execution cost, and a composite brief. Minor gaps like historical OHLCV or multi-chain on-chain analytics are not critical given the agent's stated focus.

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