x402 Crypto Market Structure

market_snapshot

Read-onlyIdempotent

What's the market doing right now? Price, funding rate, CVD, whale activity, and liquidation pressure in one call — 16 fields, no LLM overhead. Feed directly into your own models or decision logic. orderflow coverage disclosed per token. REST equivalent: POST /data (0.20 USDC).

Args:
    token: Token symbol (BTC, ETH, SOL, XRP, ADA, DOGE, AVAX, LINK, BNB, ATOM,
           DOT, ARB, SUI, OP, LTC, NEAR, TRX, BCH, SHIB, HBAR, TON, XLM, UNI, AAVE,
           AMP, ZEC)

Input Schema

TableJSON Schema

Name	Required	Description	Default
`token`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds valuable behavioral context beyond these: the exact field count (16), the REST equivalent (POST /data) with a specific cost (0.20 USDC), and a per-token orderflow coverage disclosure, which hints at potential data limitations. No contradiction with annotations.

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 and well-structured: a question-led opening, a summary of contents, a REST equivalence note, and an Args section. It avoids verbose explanations, though the phrase 'orderflow coverage disclosed per token' is somewhat cryptic and could be clearer.

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?

With one parameter and an output schema provided, the description doesn't need to detail return values. It includes practical details like cost, token list, and coverage disclosure, making it sufficiently complete for a simple snapshot tool. However, it doesn't explicitly map to sibling alternatives, which could be improved.

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

Parameters5/5

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

The input schema only defines 'token' as a string with no description (0% schema coverage). The description compensates fully by listing all supported token symbols (BTC, ETH, SOL, etc.) and implying uppercase format, which is essential for correct invocation.

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 immediately answers 'What's the market doing right now?' and enumerates specific data categories (Price, funding rate, CVD, whale activity, liquidation pressure). It distinguishes itself from sibling market tools by emphasizing raw data ('16 fields, no LLM overhead') suitable for feeding into models, implying a snapshot tool rather than an analysis or orderflow-specific tool.

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 provides clear context for when to use it: when you need raw market data directly for models or decision logic without LLM overhead. However, it does not explicitly state when not to use it or name alternatives like market_analyze or market_orderflow, leaving the choice among siblings somewhat 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

A4/5.0

Disambiguation3/5

The five market_* tools overlap in purpose—all provide market analysis for tokens—but each has a distinct focus (macro regime, full diligence, light coverage, orderflow, snapshot). The overlap is manageable, but an agent could hesitate between market_snapshot and market_orderflow since both include orderflow data. address_risk and api_info are clearly distinct.

Naming Consistency2/5

Naming conventions are inconsistent: address_risk, api_info, market_orderflow, and market_snapshot are noun_noun compounds, while market_analyze is noun_verb, and market_full/market_light are noun_adjective. There's no consistent verb_noun or pattern, making it harder to infer tool behavior from names alone.

Tool Count5/5

Seven tools is well-scoped for a market analysis server. Each tool covers a reasonable slice of functionality without excessive redundancy, and the count fits the typical 3-15 tool sweet spot.

Completeness4/5

The tool set covers the major aspects of market structure analysis: macro regime, snapshot, orderflow, full due diligence, lightweight coverage for any token, wallet risk, and API info. Minor gaps exist—such as no dedicated historical data tool or token-level risk beyond what market_full provides—but agents can work around them.

Resources

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