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LastLook Data

by io.github.zev-lll

Get Current Crypto Price

get_crypto_price
Read-onlyIdempotent

Returns the current USD price, 24h % change, market cap, and 24h volume for any supported cryptocurrency. Supported: BTC, ETH, SOL, BNB, XRP, USDT, USDC, ADA, AVAX, DOGE, DOT, MATIC, LINK, LTC, ATOM, UNI, SUI, APT, NEAR, PEPE. Source: CoinGecko. Priced at $0.02 USDC via x402 on Base.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
coinYesCrypto symbol e.g. BTC, ETH, SOL, DOGE

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesFull name
as_ofYesISO timestamp of the data fetch
symbolYesCrypto symbol
price_usdYesCurrent price in USD
change_24h_pctYes24-hour price change %
market_cap_usdYesMarket cap in USD
volume_24h_usdYes24-hour trading volume in USD

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already carry the read-only, idempotent, non-destructive hints. The description adds valuable context beyond that: the data source (CoinGecko) and the monetization/pricing model ($0.02 USDC via x402 on Base). This gives the agent useful operational knowledge not present in the annotations.

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?

The description is compact and front-loaded with the core purpose. The supported coin list is necessary for the agent to know valid inputs, and the source and pricing info are each one short clause. Every sentence earns its place with no filler or redundancy.

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?

The combination of an output schema (not shown but present) and the annotations already covers return structure and safety. The description fills in the supported universe, data source, and cost model. It could hint at whether prices are live or delayed, but for a simple lookup tool this is adequately complete.

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?

The schema already fully describes the parameter: the enum lists every supported coin, and the schema-level description gives examples. The main description repeats the supported list verbatim, adding no extra meaning. According to the baseline rule for high schema coverage, a 3 is appropriate.

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 opens with a specific verb ('Returns') and clearly names the resource ('current USD price') along with the exact data fields (price, 24h % change, market cap, 24h volume). The word 'current' distinguishes it from get_crypto_history, and the supported coin list further disambiguates the scope.

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

Usage Guidelines4/5

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

The description establishes clear context (current price for a fixed set of supported cryptocurrencies) and implicitly signals this is for current data, not historical. It does not explicitly name alternatives or exclusions such as 'use get_crypto_history for historical data,' so it stops short of a 5.

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

A3.9/5.0
Disambiguation3/5

The tool set has several overlapping functions, particularly among the bundle tools (e.g., get_bundle_context_brief vs get_bundle_macro both provide macro indicators, and get_bundle_rate_environment overlaps with get_yield_curve and get_policy_spread). Individual current/history/date tools are distinct but some redundancy exists (e.g., get_treasury_yield_current vs get_current_value for DGS30). Descriptions help differentiate purposes, but agents may still hesitate when selecting between similar bundles.

Naming Consistency4/5

All tool names begin with the verb 'get_' and use snake_case, creating a consistent pattern. The bundle tools are uniformly prefixed with 'get_bundle_', and individual data tools follow a get_[entity]_[modifier] structure (e.g., get_fx_rate_current, get_fx_rate_by_date, get_fx_rate_series). Minor deviations exist (e.g., get_series, get_current_value, get_value_by_date are less descriptive of the underlying entity), but overall the naming is predictable and readable.

Tool Count3/5

With 24 tools, the server is on the heavy side of the typical range. The broad domain (macro data, mortgage, crypto, FX, treasury, EDGAR) justifies many tools, but some could potentially be consolidated (e.g., individual rate tools vs rate bundles). The count does not feel overwhelming, but it is borderline heavy.

Completeness4/5

The server covers a wide range of economic and financial data with both bundled and granular views. It includes current, historical, and date-specific retrievals for FRED series, FX, and crypto, plus specialized tools for mortgages, recession, and yield curves. Minor gaps exist, such as no way to list all supported FRED series or full financial statements for EDGAR, but the core lifecycle of data querying is well covered.

Resources