x402 Crypto Market Structure

market_full

Read-onlyIdempotent

Full pre-trade diligence in one call. Gets all market and orderflow data, then makes a grounded judgment: BULLISH/BEARISH/NEUTRAL stance, ACCUMULATION/DISTRIBUTION signal, LOW/MODERATE/HIGH/CRITICAL risk level, and a verdict that cites actual data values — not vibes. Use when you want a single answer rather than assembling the pieces yourself. coverage disclosed per token. REST equivalent: POST /analyze/full (0.75 USDC).

Args:
    token: Token symbol (BTC, ETH, SOL, XRP, ADA, DOGE, AVAX, LINK, BNB, ATOM,
           DOT, ARB, SUI, OP, LTC, AMP, ZEC)
    context: Optional context window ('7d' or '30d').

Input Schema

TableJSON Schema

Name	Required	Description	Default
`token`	Yes
`context`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already convey read-only, idempotent, and non-destructive behavior. The description adds value by disclosing the tool makes a grounded judgment (not just raw data), cites actual data values, discloses coverage per token, and includes cost/REST info. No contradiction.

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 structured with a clear intro, use-case sentence, and delimiter-separated args. It is informative without being excessively verbose, though the fragment 'coverage disclosed per token' is slightly awkward.

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 an output schema present and annotations covering safety, the description sufficiently covers purpose, usage, parameters, and cost. It could elaborate on the response structure, but the output schema likely handles that. The ambiguous coverage statement is a minor gap.

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

Parameters4/5

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

Schema coverage is 0%, but the description compensates with an Args section listing supported token symbols and the optional context window ('7d' or '30d'). It adds meaning beyond the schema, though it could clarify default behavior when context is omitted.

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 clearly states the tool performs full pre-trade diligence, aggregating market and orderflow data to produce a stance, signal, risk level, and verdict. It distinguishes itself from siblings by emphasizing a single consolidated answer rather than assembling pieces manually.

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?

It explicitly says 'Use when you want a single answer rather than assembling the pieces yourself,' giving clear usage context. It does not name specific alternatives or provide when-not guidance, but the context is sufficient for distinguishing from sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All x402 Crypto Market Structure tools Inspect

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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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