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Crypto Market Intelligence — Prices, Trends & AI

crypto_market_intelligence
Read-only

Pull live market data for any coin or token from CoinGecko — price, market cap…. Pull live market data for any coin or token from CoinGecko — price, market cap, volume, 24h/7d/30d change, supply and category — with an AI read on momentum…

Input Schema

NameRequiredDescriptionDefault
inputNoInput for Crypto Market Intelligence — Prices, Trends & AI. See https://apify.com/noniner/crypto-market-intelligence.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

C2.8/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds only that the source is CoinGecko and that an 'AI read on momentum' is included, but says nothing about rate limits, latency, data freshness, or response shape — and with no output schema, that gap matters.

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

Conciseness2/5

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

The description text is literally duplicated with an ellipsis ('Pull live market data for any coin or token from CoinGecko — price, market cap…. Pull live market data for any coin or token from CoinGecko — price, market cap, volume...'), which wastes tokens and suggests truncation/corruption rather than a deliberate, front-loaded summary.

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

Completeness3/5

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

With no output schema, the description partially compensates by enumerating the returned data fields, which helps an agent understand what comes back. However, it omits input format, freshness, and any AI-output caveats, leaving real gaps for a nested-input actor.

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?

One optional parameter wrapped in a nested 'input' object with nominal 100% schema description coverage, though the schema description is only a URL reference. The description adds no parameter-level detail (e.g., how to pass a coin id or category), so the baseline 3 applies.

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

Purpose4/5

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

States a specific verb and resource ('Pull live market data for any coin or token') plus the concrete data fields returned (price, market cap, volume, changes, supply, category) and the data source (CoinGecko). It is clear what the tool does, though there are no crypto siblings in the list to differentiate against, so no sibling-routing credit applies.

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

Usage Guidelines2/5

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

There is no explicit guidance on when to use this tool versus alternatives, no exclusions, and no prerequisites. The mention of CoinGecko as a source is the only contextual anchor, and usage must be inferred entirely from the resource it targets.

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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