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LiveDataLink

by io.github.blackboxfoundry

crypto_compare

Read-onlyIdempotent

Compare 2-5 cryptocurrencies side by side. Shows price, 24-hour change, market cap, volume, and rank for each coin in a comparison table. Use this for 'compare bitcoin and ethereum', 'BTC vs ETH vs SOL', 'which is bigger bitcoin or ethereum?', 'compare top cryptos', 'crypto head to head', or any multi-coin comparison question.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
coinsYesCoin names or tickers, 2-5 coins. Accept either CSV string ('bitcoin,ethereum,solana') or array (['bitcoin','ethereum','solana']).

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that results are presented in a comparison table with specific fields, which is useful but does not disclose additional behavioral traits beyond what annotations already communicate.

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, front-loaded with the core action, and uses the example list to clarify intended usage without unnecessary filler. Each sentence contributes either scope, output detail, or invocation examples.

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 single-parameter read-only comparison tool, the description covers purpose, usage examples, and output content. It does not specify the currency/unit for prices or behavior on invalid coin identifiers, but these are minor gaps given the annotations and schema already handle the main operational context.

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 only parameter, coins, is fully described in the input schema with the same 2-5 count constraint and accepted formats (CSV string or array). The tool description reinforces '2-5 cryptocurrencies' but does not materially add meaning beyond the schema, so the baseline of 3 applies.

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 and resource: 'Compare 2-5 cryptocurrencies side by side.' It then enumerates the exact metrics shown (price, 24-hour change, market cap, volume, rank) in a comparison table, which clearly distinguishes it from siblings like crypto_price, crypto_info, and stock_compare.

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 provides strong context by listing example queries such as 'compare bitcoin and ethereum', 'BTC vs ETH vs SOL', and 'which is bigger bitcoin or ethereum?', and explicitly says to use it for 'any multi-coin comparison question.' It does not explicitly name alternatives or state when not to use it, but the multi-coin condition is clear.

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

B3.2/5.0
Disambiguation2/5

Many tools overlap heavily across domains: caselaw_search vs court_case_search vs court_opinion_search, caselaw_citation_lookup vs court_citation_resolver, and a cluster of company due-diligence tools (company_trust_check, counterparty_risk_score, entity_dossier, issuer_diligence_dossier, kyb_aml_evidence_case_file) that all screen a company for sanctions/risk/standing. With 290 tools, an agent will frequently face multiple equally plausible choices for the same user intent.

Naming Consistency3/5

The vast majority of tools follow a clean domain-prefix + snake_case pattern (census_, eia_, fmcsa_, npi_, cfpb_, etc.), but there are notable exceptions: entity_resolve and resolve_entity are reversed duplicates, reg_search (Federal Register) sits next to reg_cfr_search (CFR) with confusingly similar names, and carrier_monitor_recheck deviates from the carrier_vetting_* family.

Tool Count1/5

290 tools is an extreme count under any rubric, far exceeding even the 50+ threshold for the lowest score. While the group-filtering mechanism and meta-tools like list_tool_groups and search_available_datasets mitigate the practical burden, the raw surface is still massively oversized for an agent to select from accurately and efficiently.

Completeness4/5

For a read-only data-aggregation server, coverage is remarkably comprehensive across 59 domains, and generic fallbacks like cdc_dataset_query, eia_series_lookup, fred_observations, and bls_series prevent most dead ends. Minor gaps exist (a single GitHub tool, demo-only property_lookup coverage, no write/update operations anywhere), but the stated data-access purpose is well served.

Resources