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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']).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already establish the tool as read-only, idempotent, and non-destructive. The description adds value by disclosing exactly what the output contains: price, 24-hour change, market cap, volume, and rank in a comparison table. This goes beyond the annotations without contradicting them.

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 front-loaded with the core action, quickly lists the output fields, and then provides concrete query examples. No filler or redundant statements; each sentence contributes to helping the agent recognize and invoke the tool correctly.

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

Completeness5/5

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

For a simple one-parameter, read-only comparison tool with full schema coverage and rich annotations, the description is complete. It defines scope, input constraints, output contents, and usage examples, so an agent has everything needed to select and call it correctly.

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 fully documents the 'coins' parameter, including accepted formats (CSV string or array) and the 2-5 limit. The description reinforces this with examples but does not add meaning beyond what the schema already provides, so the baseline score of 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 and resource: 'Compare 2-5 cryptocurrencies side by side.' It is clearly a multi-coin comparison tool, distinguished from siblings like crypto_price, crypto_info, and crypto_trending by the explicit comparison-table framing and multi-coin examples.

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 gives explicit usage triggers with 'Use this for' followed by concrete query examples such as 'BTC vs ETH vs SOL' and 'which is bigger bitcoin or ethereum?' It clearly implies when to choose this tool, though it does not explicitly name sibling alternatives or state when not to use it.

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

B3.3/5.0
Disambiguation2/5

Several tool clusters overlap heavily—company due-diligence and risk tools (counterparty_risk_score, company_trust_check, entity_dossier, issuer_diligence_dossier, resolve_entity, entity_resolve), carrier vetting tools, sanctions screening tools, and recall tools all have subtle boundary distinctions. While descriptions are detailed, an agent navigating 294 tools will frequently struggle to pick the right one.

Naming Consistency3/5

Most tools follow a readable snake_case domain-prefix pattern (fdic_, edgar_, sanctions_, congress_), which helps. However, verb placement is inconsistent—search_available_datasets vs cdc_dataset_query, resolve_entity vs entity_resolve—and synonyms like search, lookup, get, detail, fetch, and status are used interchangeably.

Tool Count1/5

294 tools is an extreme number for a single MCP server, far beyond what an agent can reliably hold in context or select from accurately. The presence of tool-group discovery helpers mitigates but does not solve the fundamental scale problem.

Completeness4/5

The data breadth is genuinely extensive, covering finance, health, legal, real estate, transportation, energy, cyber, education, and many other domains, often with generic query fallbacks. Still, some capabilities are shallow or incomplete—package tracking stops at a link, property tools are demo-only in places, and caselaw coverage is limited—so it is not a fully complete surface.